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New, Improved, Comprehensive, and Automated Driver's License Test and Vision Screening System

Final Report 559(1)

Prepared by:

ESRA Consulting Corporation™ 

1650 South Dixie Highway, Third Floor 

Boca Raton, Florida 33432 USA

MAY 2005

Prepared for:

Arizona Department of Transportation 

206 South 17th Avenue Phoenix, Arizona 85007 

in cooperation with

U.S. Department of Transportation Federal Highway Administration

The contents of the report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The authors assume no liability for the use or misuse of any information, opinions, or conclusions contained in this report. The contents do not necessarily reflect the official views or policies of the Arizona Department of Transportation or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. Trade or manufacturers’ names which may appear herein are cited only because they are considered essential to the objectives of the report. The

U.S. Government and The State of Arizona do not endorse products or manufacturers.

ESRA CONSULTING CORPORATION DISCLAIMER

Neither ESRA Consulting Corporation (ESRA), its affiliates, its associates, nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product or process disclosed, or represents that its use would not infringe privately owned rights. References herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by ESRA or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of ESRA or any agency thereof. This report is for informational purposes only. Readers are encouraged to confirm the information contained herein with other sources. The information is not intended to replace medical advice offered by physicians. Reliance on any information in this report is solely at your own risk. ESRA Consulting Corporation is not responsible or liable for any direct, indirect, consequential, special, exemplary, or other damages arising from any use of any product, information, idea, or instruction contained in this report and all publications and presentations and/ or implementations therefrom.

Notice is hereby provided that a patent application has been filed on one or more of the systems and methods described herein.

Notice is hereby provided that ESRA may be involved in development and/ or marketing of products in the systems and/ or methods described herein.

In the event that consideration is given to any component in the system described herein in which ESRA may have a marketing arrangement or other involvement, at the time of such consideration, full disclosure will made.

Technical Report Documentation Page

1. Report No. FHWA-AZ-04-559(1)

2. Government Accession No.

3. Recipient’s Catalog No.

4. Title and Subtitle                                      SPR 559 - New, Improved, Comprehensive, and Automated Driver’s License Test and Vision Screening System

5. Report Date May 2005

6. Performing Organization Code

7. Authors                                                    Sandy H. Straus

8. Performing Organization Report No.

9. Performing Organization Name and Address                                                     ESRA Consulting Corporation        1650 South Dixie Highway, 3rd Floor Boca Raton, Florida 33432                (561) 361-0004 http://www.esracorp.com

10. Work Unit No.

11. Contract or Grant No. SPR-PL-1-(61) 559

12. Sponsoring Agency Name and Address                                                 ARIZONA DEPARTMENT OF TRANSPORTATION 206 S. 17TH AVENUE PHOENIX, ARIZONA 85007                   Project Manager: John Semmens

13.Type of Report and Period Covered

14. Sponsoring Agency Code

15. Supplementary Notes Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration

16. Abstract 

This one-of-a-kind comprehensive study highlights the importance of automated testing techniques and the significance of vision screening measures other than standard visual acuity testing for assessing all drivers and, in particular, at-risk drivers and older drivers. Non-automated tests tend to be subjective, time-consuming, costly, and heavily reliant on the experience of the examiner. Due to the high collision, injury, and fatality rates of all drivers in the State of Arizona, and the disproportionate number of at-fault older drivers and collision risks in the States of Arizona and Florida, new and automated screening methodologies and vision standards are now needed to promote road safety, predict visual impairment, and evaluate possible restriction or confiscation of driver’s licenses. This study demonstrates that environmental factors and manner of collisions increase in collision involvement for drivers between ages 50 to 59 years in both Arizona and Florida. Drivers age 80 to 89 years in both states are most likely at-fault in collisions compared to all other age cohorts. These results are consistent among drivers cited for collision involvement due to visual defects. Our findings, which span an 11- year period from 1991 to 2001, not only apply to Arizona and Florida, two states with some of the largest proportions of older individuals in the United States, but, as our global survey of motor vehicle bureau directors or their representatives of the United States, Commonwealth of Puerto Rico, United Kingdom, Canada, New Zealand, and Australia illustrate, any state, country, province, territory, commonwealth, or nation with an increasing number of older drivers. A pilot study, to follow, ultimately allows for the implementation of effective strategies for screening of visual impairment and eye disease in all Arizona drivers. Snellen acuity, the most widely used vision testing measure, accounts for less than 0.1 percent of the visual field and fails to quantify contrast sensitivity and color vision (Fink and Sadun, 2004), two of several visual parameters needed for safe driving. It is recommended that at-risk and older drivers in Arizona are tested for vision through a newly designed system of measures provided by two automated tests (to test vision condition and function) and one driving simulator (to assess eye status). Hence we integrate it into a larger system and provide additional recommendations as these relate to motor vehicle operation skills and cognition. These automated systems and methodologies may ultimately serve as a prototype of transportation license testing improvements for all other states, countries, and agencies (e.g., aviation, rail, maritime, commercial vehicles, etc.) to follow. Such techniques may also reduce the incidence of fraudulent schemes and issuances of driver’s licenses, commercial driver’s licenses, and hazardous materials transportation licenses.

17. Key Words                                     older driver, at-risk driver, driver’s license test, UFOV, RAIR, Relative Accident Involvement Ratio, probabilistic risk assessment, visual acuity, driving simulator, vision test, dementia, Alzheimer’s Disease, Parkinson’s Disease, Macular Degeneration, Arizona, Florida, ESRA Dynamic Vision Assessment for Transportation, license renewal, automated testing, vision screening system, ESRA DVAT, ESRA VAPT, ESRA Vision Assessment Procedure for Transportation, simulator sickness, flashback effect, aftereffect, cybersickness, ESRA DAT, driver license test procedure, transportation license test

18. Distribution Statement Document is available to the U.S. public through the National Technical Information Service, Springfield, Virginia, 22161

23. Registrant’s Seal

19. Security Classification Unclassified

20. Security Classification Unclassified

21. No. of Pages 438

22. Price

The ESRA DAT ™ System is developed by:

ESRA Consulting Corporation

ESRA DAT ™ Sales Division

1650 South Dixie Highway, Third Floor

Boca Raton, Florida 33432

USA

Telephone:     (561) 361-0004

Arizona Fax:  (520) 844-8555

e-mail:  dat@esracorp.com

web:      http://www.esracorp.com  

I dedicate this report to the memory of Max, my grandfather, a pedestrian statistic. May this report serve as a testament to his legacy. He is sorely missed.

This one is for you, Papa.

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TABLE OF CONTENTS

Executive Summary

Implementation.

Introduction.

Purpose.

Background.

Project Overview.

Review of Literature.

Introduction.

The Older Populations of Arizona and Florida.

Older Drivers In The News.

Vision Impairment

Affected Eye Structures.

Visual Acuity.

Contrast Sensitivity.

Color Vision.

Some Diseases Of The Eyes.

Refractive Error.

Infectious Disorders of the Eye.

Nutritional And Metabolic Factors.

Alzheimer’s Disease, Dementia, and Driving.

Some Driver’s License Vision Testing Policies:  An Overview.

Vision Testing:  Self Versus Other.

Field Of Vision Testing.

Older Versus Younger Drivers.

SURVEY OF DRIVER’S LICENSE BUREAU DIRECTORS OR THEIR REPRESENTATIVES.

Analysis of Collision Data

Introduction.

Methodology.

The Framework.

Comparison of Relative Accident Involvement Ratio (RAIR) of Collisions of Arizona and Florida Drivers,  Years 1991 TO 2001.

Bathtub Curves.

Descriptive Statistics and Calculated Risks of Violations/Behavior-Related Collisions in the State of Arizona,  Years 1991 to 2001.

COMPARISON OF AVERAGE INDIVIDUAL RISKS OF COLLISIONS, INJURIES, AND FATALITIES OF ARIZONA AND FLORIDA DRIVERS, YEARS 1991 to 2001.

REVIEWS OF VISION TESTS AND DRIVING SIMULATORS.

Introduction.

The History and Future of Vision Tests.

Vision Screening Tests.

Vision Screening Methods in Other Settings.

Recommended Vision Screening Equipment.

Driving Simulators:  Yesterday and Today.

From the Past to the Present

Research, Training, and Screening Usage.

Simulator Sickness and Aftereffects.

What is simulator sickness?.

Aftereffects.

Flashback Effects.

Cyberadaptation Syndrome and Simulator Adaptation Syndrome.

Factors of Simulator Sickness.

Simulator Sickness Studies.

The Simulator Sickness Questionnaire.

Field of View and Flicker.

Gender.

Incidence of simulator sickness.

Impacts of Cybersickness.

Studies of At-Risk Drivers.

Simulator Sickness Mitigation Strategies.

Future Simulator Sickness Studies.

Safety Recommendations.

Recent and Current Driving Simulator Research

Recommended Driving Simulators

CONCLUSION..

RECOMMENDATIONS.

Vision Screening System..

Cognition Test

Knowledge Test

Driving Test

Driver’s License Renewal

Additional Recommendations.

Implementation.

Benefits of ESRA DVAT ™.

REFERENCES.

APPENDIX A:  Horizontal section of the human eyeball and some common conditions that may affect it.

APPENDIX  B:  RESULTS OF GLOBAL SURVEY OF DRIVER’S LICENSE DIRECTORS OR THEIR REPRESENTATIVES,  YEAR 2004.

APPENDIX  C:  COLLISIONS IN ARIZONA, YEARS 1991 to  2001.

APPENDIX  D:  DESCRIPTIVE STATISTICS OF COLLISIONS, FATALITIES, AND INJURIES OF ARIZONA AND FLORIDA DRIVERS, YEARS 1991 to 2001.

APPENDIX  E: OVERVIEW OF ARIZONA AND FLORIDA DRIVER’S LICENSEES, YEARS 1991 to 2001 

APPENDIX  F:  COMPARATIVE RATES OF COLLISIONS, FATALITIES, AND INJURIES OF ARIZONA AND FLORIDA DRIVERS, YEARS 1991 to  2001.

APPENDIX G:   COMPARISON OF RELATIVE ACCIDENT INVOLVEMENT RATIO (RAIR) OF COLLISIONS OF ARIZONA AND FLORIDA DRIVERS,  YEARS 1991 to 2001.

APPENDIX H:   RELATIVE ACCIDENT INVOLVEMENT RATIO OF ARIZONA DRIVERS WITH CORRECTIVE LENSES, INVOLVED COLLISIONS,

YEARS 1991 to  2001.

APPENDIX I:   RELATIVE ACCIDENT INVOLVEMENT RATIO OF FLORIDA DRIVERS ASSOCIATED WITH  INJURIES, YEARS 1991 to 2001.

APPENDIX  J:   RELATIVE ACCIDENT INVOLVEMENT RATIO OF FLORIDA DRIVERS ASSOCIATED WITH  FATALITIES YEARS 1991 to 2001.

APPENDIX K: RELATIVE ACCIDENT INVOLVEMENT RATIO OF FLORIDA DRIVERS ASSOCIATED WITH  COLLISIONS, YEARS 1991 to 2001.

APPENDIX L: DESCRIPTIVE STATISTICS OF WEATHER-RELATED COLLISIONS IN THE STATE OF ARIZONA,  YEARS 1991 to 2001.

APPENDIX M: DESCRIPTIVE STATISTICS OF LIGHT-RELATED COLLISIONS IN THE  STATE OF ARIZONA, YEARS 1991 to 2001.

APPENDIX  N: DESCRIPTIVE STATISTICS OF MANNER OF COLLISIONS IN THE STATE OF ARIZONA, Years 1991 to 2001.

APPENDIX O: DESCRIPTIVE STATISTICS OF RESTRICTIONS-RELATED COLLISIONS IN THE STATE OF ARIZONA, YEARS 1991 TO 2001.

APPENDIX P: DESCRIPTIVE STATISTICS AND CALCULATED RISKS OF VIOLATIONS / BEHAVIOR-RELATED COLLISIONS IN THE STATE OF ARIZONA, YEARS 1991 to 2001.

APPENDIX Q:  COMPARISON OF AVERAGE INDIVIDUAL RISKS OF COLLISIONS, INJURIES, AND FATALITIES OF ARIZONA AND FLORIDA DRIVERS, YEARS 1991 to 2001.

APPENDIX R: ARIZONA COLLISION RATES BY RESTRICTIONS, VIOLATIONS, AND BEHAVIORS, YEARS 1991 to 2001.

APPENDIX S: VISION SCREENING DEVICES.

APPENDIX T: DRIVING SIMULATORS.

APPENDIX U: COMPLETED GLOBAL SURVEYS.

United States of America and Commonwealth of Puerto Rico.

United Kingdom..

Canada.

Australia.

New Zealand.

APPENDIX  V:  COPY OF THE SURVEY FORMS.

ACKNOWLEDGEMENTS.

   
TABLES

 

 

Table 1

The Haddon Matrix

Table 2

Thresholds of Annual Fatality Risk Levels According to Otway and Erdmann

Table 3

Model and Special Features of Vision Testing Equipment

Table 4

Model and Special Features of Driving Simulators

 

FIGURES

 

 

Figure 1

Horizontal section of the human eyeball and some common conditions that may affect it.

Figure 2

The Bathtub Curve

Figure 3

Comparison of Left Turn Manner of Collisions Among Drivers in Arizona and Florida for years 1991 to 2001

Figure 4

Comparison of Dawn or Dusk Related Collisions Among Drivers in Arizona and Florida for years 1991 to 2001

Figure 5

Comparison of Collisions Among Drivers with Visual Defects in Arizona and Florida for years 1991 to 2001

Figure 6

ESRA Vision Assessment Procedure for Transportation™

(ESRA VAPT™)

Figure 7

ESRA Dynamic Vision Testing for Transportation™ 

(ESRA DVAT™)

Figure 8

Figure 8.  ESRA Dynamic Assessment for Transportation

(ESRA DAT ™)

 

GLOSSARY OF ACRONYMS

 

 

3DAGT            3-Dimensional Amsler Grid Test

AAA                American Automobile Association

AAMVA          American Association of Motor Vehicle Administrators

AD                   Alzheimer’s Disease

ADL                Activities of Daily Living

ADOT             The Arizona Department of Transportation

AION              nterior Ischemic Optic Neuropathy

AMD               Age-Related Macular Degeneration

AUS                Australia

AZ                   Arizona

CA                   Canada

CMV               Cytomegalovirus Retinitis

CPR                 Commonwealth of Puerto Rico

DAT                ESRA Dynamic Assessment for Transportation™ (ESRA DAT ™)

DETR              Department of the Environment, Transport and the Regions  (UK)

DfT                  United Kingdom Department of Transport

DMV               Department of Motor Vehicles

DVAT              ESRA Dynamic Vision Assessment for Transportation™

ESRA              ESRA Consulting Corporation

FAA                Federal Aviation Administration

FL                    Florida

HIV                 Human Immunodeficiency Virus

MIN                minimum

MAX               maximum

MVD               Motor Vehicle Division

NADS             National Advanced Driving Simulator

NHTSA           National Highway Traffic Safety Administration

NZ                   New Zealand

PCTL               percentile

PRT                 Perception Response Time

RAIR               Relative Accident Involvement Ratio

SAS                 Simulator Adaptation Syndrome

    S      SIREN             Simulator for Interdisciplinary Research in Ergonomics and Neuroscience

SSQ    SSQ                 Simulator Sickness Questionnaire

STD                 standard deviation

UFOV             Useful Field of View™

UK                  United Kingdom

US                   United States

USA                United States of America

VACS              Visual Acuity and Contrast Sensitivity Tests

VAPT              ESRA Vision Assessment Procedure for Transportation™

 

EXECUTIVE SUMMARY

This is the first study of its kind to present new, comprehensive, and automated testing systems with tremendous potential to revolutionize transportation licensing policies and procedures. We offer global survey development and implementation, literature reviews, and a comprehensive study of driving risks commonly associated with aging and disease in two states with significant proportions of older drivers. While the 65 years and older age group accounts for approximately 13 percent of the population of Arizona, it now forms the third fastest-growing population of age 65 years and over in the United States (see Hetzel and Smith, 2001). Similarly, Florida, has a fast-growing and significant population, at 17.6 percent, of age 65 years and older cohorts. Both states rank eighth among the top 10 causes of death through unintentional injuries for the ages 65 to 85 years population. Vehicle traffic accidents represent the largest number of these unintentional injuries and exceed the U.S. average (Centers for Disease Control and Prevention, 2003). Older drivers constitute the fastest growing segment of the driver’s licensees. Road safety implications prevail as older drivers, when compared to young or middle-age drivers, reportedly account for a higher number of collisions per distance traveled (Stamatiadis and Deacon, 1995). We effectively address this situation through analyses of the collision data trends and risks of these older drivers, comparison of these results with drivers of all other age groups over an 11-year period (1991 to 2001), and surveys of the driver’s license vision test practices of all 50 U.S. States, Commonwealth of Puerto Rico, Canada, Australia, United Kingdom, and New Zealand (henceforth referred to as “other countries”). Use of this information can be applied to develop technologies and measurement criteria for a visual acuity pilot test. Consequently, the results of this comprehensive study may not only benefit the State of Arizona, but also, ultimately, provide a prototype for nationwide transportation license reforms. ADOT is the first agency to commission such a unique, scientific study to promote motorist safety in Arizona and to benefit any country, state, commonwealth, province, territory, or nation with a burgeoning population of older drivers. The new systems and procedures ESRA presents may also reduce the incidence of fraudulent schemes and issuances of driver’s licenses, commercial driver’s licenses, and hazardous materials transportation licenses.

This report is divided into ten main sections and 22 appendices. Appendices (B,U, V) include Tables and Figures presenting the results of our global survey of directors or their representatives of driver’s licensing agencies in the Australia, Canada, Commonwealth of Puerto Rico, New Zealand, United Kingdom, and the United States in the year 2004. Tables and Figures accompany detailed explanations in Appendices B through R where trends and risks of driver collisions, injuries, and fatalities within the States of Arizona and Florida over an 11-year period, years 1991 to 2001, are documented and reported.

First we review recent collision events and how these have impacted older driver licensing issues. We also explore existing literature to highlight some of the possible factors affecting older driver safety, in particular, vision, and the history of studies that relate to driver’s license vision testing methods and policies. We find that driver’s license vision testing methods and policies vary from state to state and country to country. We determine that a number of states shorten the period between both driver’s license application and renewal vision tests. While this may, in the short term, allow for limited identification of drivers with visual impairments, it fails, in the long term, to significantly improve the actual vision testing process and screen the most at-risk drivers. We also find that major reforms are needed in defining vision standards in order to improve current vision testing methodologies since visual acuity, the most common measurement of ranges of vision loss (International Council of Ophthalmology, 2002), accounts for less than 0.1 percent of the visual field and fails to quantify contrast sensitivity and color vision (Fink and Sadun, 2004). Although the latter constitute two of several visual parameters needed for safe driving, we suggest that these new vision standards incorporate visual acuity measurements. We therefore seek to design a new vision testing procedure through evaluation of the history and application of certain tests and driving simulators. We demonstrate that current vision testing methodologies are inadequate and most driving simulators are limited to research usage. However, we also recommend a vision screening system to study eye conditions, diseases, and functions and how these can benefit any at-risk driver, especially older drivers and drivers with dementia and other neurological conditions that may affect driving performance. We include diagrams of our conceptualized vision test system design, the ESRA Vision Assessment Procedure for Transportation™ (ESRA VAPT™) (Figure 6) and the ESRA Dynamic Vision Assessment for Transportation (ESRA DVAT™) (Figure 7). We also introduce the ESRA Dynamic Assessment for Transportation (ESRA DAT™) (Figure 8), a potentially thorough and cost-effective test of some of the most important features applicable to other areas of transportation. Hence the results of our study may impact driver’s license testing procedure, policy, and legislation and the transportation industry overall.

Second, we provide a brief overview of our survey methodology of the driver’s license vision test practices. Our global survey (Appendix V) and results are tabulated (Appendices B and U) and described in entirety in the appendices. Although we identify some recent pilot studies carried out at the California Department of Motor Vehicles and the New Mexico Motor Vehicles Division and various reports published through the United Kingdom Department of Transport, our surveys reveal that no comprehensive research or large-scale testing has been conducted over the last decade to validate use of current vision testing methodologies in driver’s license bureaus in Australia, Canada, New Zealand, United Kingdom, and the United States. Overall, our data show that all national and international driver’s license bureau directors or their representatives (henceforward referred to as “officials”) who participated in our study report offer the following broad observations:

·       No driver’s license bureau offers automated vision testing programs.

·       The majority of U.S. states use Optec 1000 vision screening equipment in whole, or in part, for screening drivers at license application or renewal. The other countries surveyed use Optec 2000, a more updated model.

·       There are no consistent vision testing approaches or standards in the U.S. driver’s license agencies. Each state operates independent of the others. These findings support earlier results described by Demers-Turco (1996) and Peli and Peli (2002).

·       Most officials in the United States and in other countries acknowledge that their current vision testing methodologies are either inadequate or inaccurate. This finding confirms conclusions discussed by McCloskey et al. (1994) on the topic of vision testing in driver’s license bureaus and optometric settings in the United States.

·       No vision tests at driver’s license bureaus in the United States and other countries include a screening component for glaucoma or Age-Relate Macular Degeneration (AMD), two of the fastest growing diseases that can result in vision loss.

·       No vision tests at driver’s license bureaus in the United States and other countries offer “Dynamic Vision Assessment for Drivers” (ESRA DVAT ™) that include responses to ambient light and simulated weather conditions, useful for the vision screening of at-risk drivers, novice drivers, and older drivers.

Third, we briefly discuss some of the ways that collision data are analyzed and how these methods are applied to our study.

Fourth, we evaluate the method of Relative Accident Involvement Ratio (RAIR) to measure and compare the quotient of at-fault drivers of a specific age group to the corresponding number of not-at-fault drivers (no-fault drivers), in the states of Arizona and Florida. RAIR provides us with a rapid and refined method of quantification and comparison of large sets of data, in our case, millions of collisions, between two different

U.S. states, over an 11-year period, 1991 to 2001. RAIR also allows us to analyze which drivers, by age cohorts, are most likely to be at-fault in a motor vehicle collision. The data are obtained through databases of two-vehicle accidents. These include the databases of Accident Location Identification and Surveillance System (ALISS) of Arizona and the Highway Safety and Motor Vehicle Department of Florida. The data are acquired through the Arizona Traffic Accident Report and Florida Long Form Traffic Crash Reports provided by law enforcement agents in both states. We investigate the effects of driver age cohorts on collision events and evaluate the impacts of year, lighting, weather, and contributing causes. We highlight our findings as follows:

·       The RAIR values for Arizona and Florida drivers typically and graphically appear as bathtub curves. The three distinct areas of the bathtub curve are useful for identifying properties of product life (reliability theory and analysis) and retirement, and, as we show, applying to transportation engineering concepts. (These graphs are merely identified as “U-shape distributions” in other literature.)

·       The Wearout Period, a period of increased decline, tends to initiate within the Arizona and Florida driver cohorts at about age 50 to 59 years. Since the onset of the Wearout Period also appears in drivers with corrective lenses restrictions, we suggest frequent vision testing for license renewal applicants at and over age 50 years (every two years) and at and over age 70 years (every year).

·        The characteristically long Early Failure Period (often called “Infant Mortality Period” in reliability engineering literature) and high at-fault collision involvement susceptibility we observe among the cohorts age 16 to 19 years in

·        Arizona and Florida suggests that these drivers require more comprehensive vision testing every two years. Novice drivers may especially benefit from vision status testing through the ESRA DVAT ™ due to a lack of experience navigating roads in ambient light and weather conditions.

·       We establish a link between drivers with visual defects and collision risk as it relates to environmental and driving performance behaviors.

·       Drivers ages 80 to 89 years are about twice as likely to be at-fault when compared to the cohorts ages 16 to 19 years in the following categories of collisions:

·       angle manner of collisions (Arizona, Florida)

·       clear weather-related collision (Arizona, Florida)

·       cloudy weather-related collision (Florida)

·       darkness-related collision (Arizona, Florida)

·       daylight-related collision (Arizona, Florida)

·       fog-related collision (Arizona, Florida)

·       head-on manner of collisions (Arizona, Florida)

·       rain-related collision (Arizona, Florida)

·       rear end collision (Arizona)

·       sideswipe manner of collision (Arizona, Florida)

·       Drivers ages 90 years and older are about twice as likely to be at-fault when compared to the cohorts ages 16 to 19 years in the following categories of collisions:

·       head-on manner of collisions (Arizona)

·       cloudy weather-related collision (Arizona)

·       dawn or dusk-related collision (Arizona, Florida)

·       Arizona drivers and Florida drivers age 90 years and older with visual defects are about twice as likely to be at-fault in a corrective lenses restriction-related collision than the cohorts ages 16 to 19 years. This seems to demonstrate that these drivers are most likely impacted by dawn and dusk, yet, the shape of these skewed bathtub-shape curves also reveals that various lighting, weather, and manners of collision may also significantly affect vision, especially visual defects.

·       Florida drivers age 90 years and older are, according to the highest RAIR values, seven times as likely to be at-fault in collision involvement due to corrective lenses restrictions than drivers age 16 to 19 years (Figures 44, 52, Appendix H). The severity of visual defects in older drivers may account for these extraordinarily higher collision risks.

·       Both Arizona and Florida drivers ages 80 to 89 years are about three times as likely to be at-fault in left-turn manner of collisions compared to the drivers age 16 to 19 years in these states.

·       Arizona and Florida drivers, age 80 years and over are more likely at-fault in collisions due to corrective lenses restrictions than any other age cohorts (Figures 44 to 52, Appendix H).

·       We find that Arizona drivers ages 80 to 89 years are most likely at-fault in collision involvement associated with disregarding traffic signal, driving in opposing traffic lane, following too closely, being inattentive, running stop signs, passing in a no-pass zone, making improper turns and unsafe lane changes. These violations and behaviors may be largely attributed to vision impairments.

Fifth, we report the results of our calculations and analyses of collision rates per 100,000 licensed Arizona drivers on the basis of driver’s license restrictions over an 11-year period, from 1991 to 2001.We select drivers ages 25 to 34 years as a baseline since this group surpasses all other age groups with the greatest number of collisions, injuries, and fatalities in both the States of Arizona and Florida. This group is also one of the most populous. We find that Arizona drivers age 75 years and older have significantly higher collision rates than the drivers ages 25 to 34 years. For example,

Over an 11-year period, from 1991 to 2001, the collision rate, per 100,000 licensed Arizona drivers age 75 years and older, may be as high as seven times the rate for drivers age 25 to 34 years (Figure 82, Appendix B) on the basis of the driver’s license restriction “daylight hours”.

Sixth, we introduce the Average Individual Risk calculations. These allow us to rank risks and prioritize measures to avert collisions, injuries, and fatalities. We, therefore, determine the following:

·       The Arizona driver age groups with the greatest Average Individual Risk of Fatalities include the age 75 years and older cohorts (6.65E-04).

·       Arizona drivers in all age cohorts have higher Average Individual Risks of Collisions than Florida drivers.

·       Arizona drivers age 75 years and older are, on average, more than four more times as likely to be at an individual risk of collision than Florida drivers of the same age group (Table 95).

·       Average Risks of Collisions, Average Individual Risk of Injuries, and Average Individual Risk of Fatalities are highest among Arizona drivers (Table 96).

·       We find that the greatest individual risks for Arizona drivers age 80 to 89 years are attributed to: “Pass in No-Passing Zone,” “Ran Stop Sign”, and “Drove in Opposing Traffic Lane.” The greatest yearly individual risk, among these calculated risks is “Pass in No Passing Zone (Table 98).

Seventh, we examine the history and future of vision screening techniques. We highlight the following:

·       According to our global survey, no comprehensive studies have been carried out over the last 10 years to validate continued use of the vision testing methodologies currently utilized in driver’s licensing agencies. Our extensive literature review confirms this disparity of empirical data.

·       We demonstrate the need for a comprehensive and automated vision testing system to include two vision tests and one driving simulator. In combination, these offer what we call ESRA Dynamic Vision Assessment for Transportation™ (ESRA DVAT ™), a radical departure from the traditional and inadequate static visual acuity testing techniques in order to comprehensively identify, among others, at-risk drivers.

·       The ESRA Vision Assessment Procedure for Transportation™ (ESRA VAPT™) complements the vision testing component of the NHTSA “Model Driver Screening and Evaluation Program” (Staplin et al., 2003a) for a fitness to drive determination. The vision testing component of the NHTSA Model, for example, measures near and far acuity, contrast sensitivity, and visual field loss testing. The ESRA VAPT™ allows for assessment of vision condition and vision function of drivers of all ages. In addition, older drivers and at-risk drivers may be tested for vision status in order to promote safe and longer driving activities.

·       We identify the B1Max ™ VACS, a fully automated high- and low- contrast visual acuity screen. According to Staplin (2005), the reliability of this procedure is demonstrated by its use as part of the      D RIVING  H EALTH ® INVENTORY (D H I) tool, which is used for driver evaluations by the Medical Advisory Board of the Maryland Motor Vehicle Administration. It provides a quick and useful screening measure of visual deficiencies that can potentially put an end to mechanical failures and long queues associated with existing vision screening techniques in transportation licensing agencies and medical facilities. This test also powers the Roadwise Review™ home-based assessment tool released by AAA in January 2005.

·       The 3DAGT may offer a very fast and effective way to screen drivers for potential or existing brain tumors and eye diseases. Such conditions increase collision risk in drivers. The 3DAGT has been successfully deployed at the Doheny Eye Institute at the University of California since April 2000. However, it requires substantial modifications prior to implementation in any transportation licensing agency, including the Driver’s License Bureaus.

Eighth, we also review the history of driving simulators. Fifty-nine different national and international driving simulators are identified in order to select one that may satisfy criteria developed by ESRA for use in its transportation licensing systems and procedures. Recommendations are based on safety and performance records, published studies, references, and independent testing on older drivers, among other liability concerns. We report the following:

·       Some U.S. states, through both private and public educational centers and clinics, offer optional driving assessment sessions. These sessions typically include driving simulator applications, which, according to evaluations available at the Eastern Virginia Medical School (Simpson, 2004) and the University of Virginia (Pinto, 2004), may cost drivers up to $300 per evaluation.

·       These costs are prohibitive and can prevent many drivers, in particular, at-risk and older drivers, from this “hands-on” approach to assessment of vision status skills necessary for driving.

·       The addition of a driving simulator, such as the Systems Technology, Inc. models we identify, as part of the system we recommend to ADOT, will allow equal access to all at-risk drivers, regardless of income.

·       Driving simulators of the future may be a cost-effective alternative to or supplement to on-road motor vehicle driving skills tests in driver’s license bureau settings. This is a subject that requires extensive research and is beyond the scope of this study.

Ninth, we review the literature on simulator sickness and aftereffects such as flashback effects, Cyberadaptation Syndrome, and Simulator Adaptation Syndrome. We evaluate the histories of simulator sickness studies, the benefits of the Simulator Sickness Questionnaire, and the significance of field of view, flicker, and gender. The incidence of simulator sickness, the impacts of Cybersickness, studies of at-risk drivers, simulator sickness mitigation strategies, future studies, and safety recommendations are also presented.

Last, through development of the ESRA Dynamic Assessment for Transportation™ (ESRA DAT ™), we evaluate the potential for automation of other tests, such as cognition, knowledge (written), and operation skills as these may relate to driver’s license tests and other transportation license tests.

The following enhancements are therefore recommended to ADOT:

·       Work with local, state, national, and international medical and government agencies to develop a new and comprehensive vision standard to replace the very old and inadequate visual acuity standard for driver’s license issuance and renewal.

·       Proceed with an implementation phase of the automated high- and low- contrast visual acuity screen, the B1Max ™.

·       Initiate a pilot study to include the driving simulator and visual condition tests, as the other parts of the ESRA DVAT™ System as conceptualized (Figure 7). These include the Systems Technology, Inc. driving simulators and the Modified 3DAGT we identify.

·       Shorten the periods between driver’s license issuance and renewal for vision testing, in particular for drivers age 15 to 19 years (every two years), drivers age 50 to 70 years (every two years), drivers age 70 years and older (every year), and all other drivers (every four years).

·       Combine forces with medical agencies and officials, as well as other driver’s license bureaus, on developing a method of assessing scores submitted through the three different components of the system (two vision screening tests and one driving simulator) envisaged for the pre-pilot study.

As a low-cost initiative, at a minimum, the State should implement the B1Max ™ VACS, a fully high- and low- contrast visual acuity screen in transportation agencies and hospitals. The state should also work with hospitals to implement driving simulators to test the vision status of at-risk patients and others on-site once the driver simulator safety concerns that we identify, among others, are resolved. The modified 3-D Amsler Grid Test (3DAGT) should also be implemented. No independent testings of the ESRA DAT ™ System and/ or ESRA DVAT™ System, such as the products we identify were conducted to study for safety concerns. For example, there may be flash images or flashback effects associated with automated testing and driving simulator usage that need to be explored due to safety issues, among others, of drivers and other transportation licensees prior to implementation in any hospital or driver’s license bureau setting. These flashback effects may be delayed and occur while driving after driving simulator usage.

It is important to note that the use of the driving simulator(s) we propose in this procedural assessment is not to test driving skills and/ or replace on-road driver’s license tests, but to assess vision status and strategy in a simulated driving environment, following a medical assessment referral and/ or evaluation test, as a means of detecting neuropsychologic and neuromotor disorders or as a supplementary measure of screening the vision status of drivers. (Please refer to Figure 6.) Lakshiminarayanan (2000), as we discuss, has linked dementia and Alzheimer’s Disease with decreased visual acuity under low luminance.

The driving simulators we identify for possible implementation in the ESRA DVAT™ appear to offer various luminance settings, unlike traditional Snellen eye charts. More importantly, an independent panel of physicians and scientists are needed to determine the length of such simulator tests and the interpretation of these test results. Ideally, these tests need to be conducted and overseen by a licensed medical professional until guidelines are developed to allow for the automatic screening of drivers. In the future, studies and research may allow driving simulators to test driving skills and/ or replace on-road driver’s license tests.

If the vision testing modifications we identify are implemented and, after the pilot test, proven successful within the State of Arizona, then ADOT will serve as a prototype of vision testing improvements for all other states, countries, and agencies (e.g., aviation, rail, bus, agriculture, etc.) to follow.

Implementation

The estimated potential benefit of $45 million per year from implementing the full, three step-improved test is 13 times larger than the estimated $3.3 million annualized cost of the improved testing system. The magnitude of the benefit compared to the cost creates a strong argument for pursuing a further effort to explore possible implementation of the improved test. Granted, the benefits will not flow directly to ADOT-MVD in the form of funds with which to pay for implementation. Benefits will be dispersed throughout the community in the form of fewer lives lost or damaged by collisions that might have been avoided if more impaired drivers were taken off the roads. Revenues gained and costs avoided will occur in the state’s general fund. A case can be made for funding the improved driver testing procedurefrom these sources.

Note: The benefit/cost estimate was calculated by John Semmens, ADOT, from data provided by ESRA.

The ESRA DAT ™ System is developed by:

ESRA Consulting Corporation

ESRA DAT ™ Sales Division

1650 South Dixie Highway, Third Floor

Boca Raton, Florida 33432

USA

Telephone:     (561) 361-0004

Arizona Fax:  (520) 844-8555

e-mail:  dat@esracorp.com

web:      http://www.esracorp.com  

 

 

 

INTRODUCTION

Purpose

The objective of this study is ten-fold:    

1) to evaluate recent literature on cutting-edge automated driver’s license testing practices; 

2) to collect and analyze the collision and fatality data for all drivers in Arizona and Florida;

3) to survey key driver’s license bureau personnel in all 50 states and in other countries in order to assess the current automated driver’s license testing system methodology;

4) to synthesize these data as bases for measurement criteria and risk analyses to evaluate the success of a pilot test;

5) to present a newly designed experimental visual screening system offering the most potential for a comprehensive and automated driver’s license testing system demonstration project in the State of Arizona;

6) to demonstrate that a thorough measurement of the visual system is of fundamental importance to motorists everywhere 

7) to promote highway safety through improved vision screening techniques of older

drivers and at-risk visually impaired drivers. 

8) to evaluate simulator sickness and aftereffects. 

9) to offer simulator sickness mitigation strategies and suggestions for future studies.

  10) to introduce the partial and/ or complete automation of other driver’s license test components, such as cognition, knowledge (written), and/ or motor vehicle operation/driving skills. Such automation techniques may also benefit other transportation license tests.

Background

While the trends and risks of drivers in the States of Arizona and Florida are calculated and presented, this study shows that older drivers are most susceptible to at-fault automobile collisions when lighting, weather conditions, and select violations are investigated. These paradigms, combined with very high collision, injury, and fatality rates, prove that a completely new vision testing system is needed to screen at-risk drivers. Since we reviewed the driver’s license policies, practices, and testing methodologies of the entire United States, Commonwealth of Puerto Rico, Canada, Australia, United Kingdom, and New Zealand, the results of our study not only apply to Arizona and Florida, but to every state, province, territory, nation, or country that seeks to improve safety on its roads and among its motorists. This is the very first study of its kind to identify a systematic approach to driver’s license vision testing on the bases of comprehensively studying driver behavior in two U.S. states with a considerable number of older drivers, significant population growth over the last decade, and investigating numerous national and international commercial and research products and components.

Project Overview

Four components define our report: a literature review, a global survey of the directors and their representatives of driver’s license bureaus, statistical studies and risk analyses of both Arizona and Florida drivers of all ages, an evaluation of vision screening tests and driving simulators, and the presentation of a newly designed comprehensive and automated vision testing system by ESRA.

The first section contains information gathered largely through on-line searches of books, journals, newspapers, and Internet Web sites. This study includes an extensive bibliography of relevant documentation after the Appendices. The second section describes the underlying process of the global survey of the directors and their representatives of driver’s license Bureaus of all 51 U.S. states, Commonwealth of Puerto Rico, all ten provinces and three territories of Canada, six states and two territories of Australia, and all of New Zealand and the United Kingdom. The survey addressed vision testing policies and practices of these bureaus. Results are displayed in the forms of tables and figures. The surveys are included as Appendix B and Appendix V. The third section presents the analyses of collision data for all drivers provided by the Arizona Department of Transportation Traffic Records Section and the Florida Highway and Safety Motor Vehicle Department, for the 11-year period from 1991 to 2001. When possible, we illustrate our results in the Minimum Model Uniform Crash Criteria (MMUCC) standard format. Collision factors, such environmental conditions (lighting and weather), manner of collisions, and violation behavior are illustrated through the application of Relative Accident Involvement Ratios (RAIR) and probabilistic risk analyses of all age groups. We briefly summarize our results after each table and figure in Appendix C.

The fourth section introduces us to the power of Relative Accident Involvement Ratio (RAIR) and its usefulness in determining which drivers, on the bases of age, are most susceptible to at-fault collision involvement with respect to weather, lighting, and manner of collision. The fifth section provides us with an overview of the Arizona driver collision rates over an 11-year period. The sixth section highlights the Average Individual Risk calculations and its application to both Arizona and Florida drivers.

The seventh section covers some of the latest vision test equipment and driving simulators available. We review the histories of these products, highlight some of their strengths and weaknesses, and discuss ways that, as part of a system we design, they may improve safety and ultimately reduce collision risks among all drivers.

Our study supports the initiation of more comprehensive and stringent vision testing methods in order to adequately screen at-risk drivers.

REVIEW OF LITERATURE

Introduction

Vision is the fundamental way we perceive and respond to stimuli all around us. It dynamically involves sight, knowledge and reaction. Sight, a receptive ability, and an acuity measurement, allows one the ability to clearly see a target at a particular distance. Vision is estimated to account for 85 percent to 95 percent of all sensing clues in driving (American Automobile Association, 1991). Low vision often occurs when sight weakens with increasing age. Low vision principally appears in the U.S. population of age 65 years and older cohorts. Although individuals age 80 years and older comprise 8 percent of the population, they constitute 69 percent of the cases of blindness (National Eye Institute, 2004). Low vision results from congenital, genetic, or acquirable factors. The latter may be attributable to age-related deterioration, disease, medication, injury, and/or trauma. While certain diseases and conditions may target specific areas of the eye, trauma may impact all areas of the eye. According to the National Eye Institute (2004), vision disorders constitute the fourth most widespread class of disability in the United States. Vision impairment occurs when glasses, contact lenses, or surgery cannot correct the vision loss. Cataracts, Age-related Macular Degeneration (AMD), glaucoma, and diabetic retinopathy account for the four main causes of visual impairment and blindness in the United States (Desai et al., 2001). Torpey et al. (2003) indicate that visual impairment may be caused by both systemic conditions and specific eye conditions. The systemic conditions may include atherosclerotic disease (cholestrol deposits in the eye), cerebrovascular (brain blood vessel) disease or stroke, diabetes, eye infections, hypertension (high blood pressure), Human Immunodeficiency Virus (HIV), and/or vitamin A deficiency. The specific eye conditions may consist of cataracts (clouding of the lens), eye injuries, glaucoma, macular degeneration, and/or tumors (eye-related).

Congdon et al. (2003) classify visual impairment according to age-related causes (cataracts, angle-closure glaucoma, open angle glaucoma, Age-related Macular Degeneration), infectious causes (trachoma, onchocerciasis, HIV and HIV-associated infection), nutritional and metabolic causes (vitamin A deficiency, diabetes), refractive error (myopia, hyperopia), and trauma. In order to screen for any one or more of these conditions, regular eye examinations are encouraged.

This study highlights the collision risks and trends of drivers in all age groups in the states of Arizona and Florida. Both states have significant populations of older drivers and are popular tourist and retirement destinations. It seems likely that there are also an additional significant number of older drivers who drive these roads with out-of-state and foreign driver’s licenses. Baggett (2003) reports that in approximately 15 percent of accidents involving older adults, for years 1999 to 2001, the driver was not a resident of the state.

The Older Populations of Arizona and Florida

The population age 65 years and over in Arizona jumped 39.5 percent to 667,839 from 1990 to 2000, more than three times the national average. This represented the third largest U.S. population increase, preceded by Alaska (59.6 percent) and Nevada (71.5 percent). In 2000, Scottsdale, Arizona, as a city with a population of over 100,000, contained the ninth highest proportions of a population of age 65 and older in the United States, at 16.7 percent. In mid-2002, the age 65 and older age group accounted for 12.85 percent of the population of Arizona. In Florida, the population of age 65 years and older increased 18.5 percent to 2,807,597. This percentage quantity was almost half of the increase in Arizona at the same time. Yet six cities in Florida constitute the top 10 highest proportions of a population of 65 and older in the United States. (Hetzel and Smith, 2001). From 1990 to 2000, Arizona had an estimated 81.7 percent change in the number of age 85 years and older cohorts; Florida, 57.7 precent. These values were significantly higher than the U.S. national change in the number of age 85 years and older cohorts at

37.6 percent. Florida has more drivers age 90 years and older than any other state (NBC 6 News Team, 2003). The age 65 years and older population in Arizona will be 7.5 times larger 17 years from now than in 1985 (Matthias et al., 1996). By 2025, the United States Census Bureau projects the population of Arizona to reach 6,412,000; Florida, 20,710,000. By 2030, senior citizens will comprise 25 percent of the Pima County, Arizona population (Cañizo, 2003).

It is now estimated that 12.5 percent of all U.S. drivers are age 65 years and older (Farmer, 2004). By 2030, when both “Baby Boomers” and “Generation X” reach retirement age, the percentage of older drivers age 65 years and older is expected to increase to 20 percent. The group born between the years 1946 and 1964 constitutes the “Baby Boomers”. The group born between years 1965 and 1980 defines “Generation X”. Nevertheless, there are approximately 33 million drivers age 65 years and older on U.S. roads and by 2030, the number is expected to climb to almost 100 million drivers (NBC 6 News Team, 2003). According to the Centers for Disease Control and Prevention (2003), the number of fatalities of older drivers on our nation’s road will likely rise as the population of Americans 65 years and older doubles between the years 2000 and 2030 (McCarthy, 2000; Centers for Disease Control and Prevention 2003). At-risk drivers of any age group require frequent and thorough screening for visual status and the impacts of these changes on driving performance, among other areas. According to Ball (2003), visual status often defines the activities of daily living (ADL).

Older Drivers In The News

National and international attention has focused on the implementation and enforcement of stringent licensing and testing procedures for older drivers. These escalated concerns and interests often follow a spate of high-profile collisions involving older drivers and shed light on the need for improved vision screening methods and accelerated driver’s license renewal periods. We define an accelerated renewal period as one where the period between the driver’s license application and renewal or one renewal cycle to the next is considerably reduced. The licensing bureaus consider accelerated renewal periods as a time for possible intervention strategies during the driver’s license issuance and renewal process.

Between 2002 and 2004, several notable older driver involvement collisions occurred in Port Everglades, Florida; St. Petersburg, Florida; Coral Springs, Florida; Santa Monica, California; Southwest Miami-Dade County, Florida (Fred Grimm, 2003); Flagler Beach, Florida; Roseville, Minnesota (Catlin, Bill, 2003); Regina, Canada; Langley, British Columbia (Cooper, 2004); Provo, Utah; Marlborough, Massachusetts and Sydney, Australia (2005).

In most of these cases, it appears that there was either a failure to stop or confusion between use of the accelerator and brake in the motor vehicle. These issues may relate to the visual system. According to LaViola, Jr. (2000), “The visual system tells the subject a variety of information which includes that he/she is moving in a certain direction, accelerating when pressing the gas pedal and decelerating when pressing the brake.”

Lundberg et al. (1998) suggest that subtle cognitive decrements, instead of dementia, may be significantly linked to risky driving behavior on the bases of collision involvement among older drivers. However, drivers’ visual and medical conditions may have also played a pivotal role in these tragedies. Vision loss or impairment, in conjunction with cognitive decrements, may prevent these drivers from making sound and timely decisions of the best action to take when driving an automobile. Mayur et al. (2001) report that 92 percent of persons 70 years and older wear glasses. Nearly 69 percent of the cases of blindness occur in the cohorts age 80 years and older (National Eye Institute, 2004). It is possible that improved and frequent vision testing could detect some of these problems or conditions. For example, driving simulator studies merit attention for screening drivers with various forms of dementia. Chronic decrements of mental capacity that may involve progressive deterioration of behavior, memory, personality, thought, and motor functions characterize dementia. Also, certain vision tests are known to associate dementia with contrast sensitivity reduction (Rizzo et al., 1997) and patients’ responses to light (Lakshiminarayanan, 2000). Sadun and Bassi (1990) observe optic nerve damage in Alzheimer’s disease (AD) patients. This condition may contribute to various forms of glaucoma, central vision loss, peripheral vision loss, side vision loss, or vision loss. Substantial vision loss may occur and AD patients, in particular, may not recognize this difficulty unless adequately screened. As shown in Appendix B, driver’s license bureaus are not equipped to screen for eye diseases or any of the visual disorders common in AD.

These implications may also apply to other sectors of transportation—commercial vehicles, trains, and airplanes. Senior pilots occasionally make headline news when their airplanes are involved in a collision. Although the FAA requires commercial airplane pilots to retire prior to age 60 years, private pilots with licenses may fly as long as they have logged the required number of flight hours and passed the required physical and skills tests. No standard comprehensive vision tests and renewal periods exist for pilots. Yet, valid medical certificates are held by more than 3,000 pilots age 80 years and older in the United States (Pensa et al., 2003). Aviation vision tests may include general, ophthalmoscopic, pupils, and ocular motility examinations. Visual acuity may be tested through application of the Snellen-type charts; Keystone Orthoscope; Bausch & Lomb Orthorator, Titmus Vision Tester; Keystone Telebinocular; Optec 2000 Vision Tester, among others (Federal Aviation Administration, 2003).

Although the genuine cause of these newsworthy injuries and fatalities may never be known, studies must focus attention and resources on improving screening techniques at driver’s license bureaus to promote driver safety. Clearly, these recent tragedies create negative stereotypes of older drivers when every driver, in every age group, has the potentiality for risky driving behavior (Appendix B). Rather than focus on possible underlying causes of these collisions, in particular, driver’s license vision testing methods, many people and organizations unjustly seek to solely accelerate the frequency of driver’s license renewal and testing periods. Others promote participation in short-term driving skill assessment courses. These approaches only create a placebo effect because it is the actual driver’s license testing methodology, in conjunction with the frequency of driver’s license renewal and testing periods that requires improvements. Once these testing enhancements are in place, the accelerated driver’s license renewal periods and short-term driving skill assessment courses serve as supplementary and precautionary safety measures.

Vision Impairment

Vision impairment varies greatly by race and ethnicity. Although approximately 1.98 percent or 2.4 million Americans have low vision, this number is expected to grow by nearly 70 percent by 2020 due to the rise in Americans age 40 years and older (The Eye Diseases Prevalence Research Group, 2004). The 1986 to 1995 National Health Interview Survey reveals a 0.03 percent annual increase in visual impairment rates among

U.S. adults between ages 18 to 39 years (Lee, 2004). These rates are significantly higher in third-world countries where resources to tend to health and medical needs are limited.

In the United Kingdom, it is estimated that undetected reduced vision exists in up to half of the older people there. While many of these people have treatable visual problems, they do not have regular optometric examinations. Evans and Rowlands (2004) suggest annual visual screening on people age 75 years and older. Clearly, the percentage of older drivers with correctable visual impairment in the United Kingdom may exceed 50 percent on the basis of driver’s license policies and vision screening tests there.

Affected Eye Structures

According to Congdon et al. (2003), visual impairments affect a variety of ocular structures. Some of these, in particular the age-related causes (i.e., Age-related Macular Degeneration, angle-closure glaucoma, cataracts, and open-angle glaucoma) are illustrated in Figure 1. Others we shall briefly describe:

Infectious Causes

o HIV and HIV-associated infection:

Choroid, cornea, lacrimal gland, optic nerve, retina.

o Onchocerciasis:

Choroid, ciliary body, cornea, iris, macula, optic nerve, retina, trabecular meshwork

o Trachoma:

Cornea, eyelashes, eyelids

Nutritional and Metabolic Factors

o Diabetes:

Lens, macula, optic nerve, retina, trabecular meshwork, vitreous body

o Vitamin A deficiency:

Conjunctiva, cornea, retina

Refractive Error

a.        o Myopia:
lens, sclera, retina

b.       o Hyperopia:

lens, sclera, retina

Visual Acuity

Visual acuity refers to spatial resolution or the measure of one’s vision with respect to clarity, sharpness, or sight ability. This ability results from the coherent focus of light from the region of the cornea on to the retina of the eye (Garcia, et al., 1999). Spatial resolution allows one to discern objects, read text, and interpret symbols and signage. Although these functions are paramount to safe driving practices at any time and anywhere, many drivers are visually deficient due to the aging processes, heredity, medication, or trauma. A driver of any age compromises the safe operation of a motor vehicle when medical or pharmaceutical conditions prevail. Cataracts, diabetic retinopathy, glaucoma, and macular degeneration, among other vision loss conditions (Gottleib, et al. 1997) may weaken color perception, contrast sensitivity, depth perception, glare recovery, or peripheral vision components. Ultimately, these vision impairments elevate the risks of traffic collisions and violations. Visual acuity varies greatly by race and ethnicity. Problems with visual acuity affect more than 2.4 million Americans (1.98 percent) age 40 years and over (Taylor and Mitchell, 2004).

In most states, the measurement of visual acuity, a primary gauge of the extent of functional impairment due to vision loss (National Research Council, 2002), is required to pass a driver’s license test. At a standard distance, a patient views the Snellen Eye Chart, a letter chart that is nearly universal in its application to clinical and research usages. The Snellen Eye Chart, developed in 1862 by Dr. Hermann Snellen, a Dutch ophthalmologist, may today include a series of letters or letters and numbers, with the largest at the top. Snellen-type charts are generally prescribed under ideal conditions (daytime lighting) and the absence of extraneous light sources. According to the National Research Council (2002), the results of this visual acuity test “…are usually expressed in Snellen notation,… the ratio of the test distance to the distance at which the critical detail of the smallest optotype resolved would subtend 1 minute of visual angle.” Optotypes refer to the letters, numbers, and symbols that assess the function of different retinal areas.

Although visual loss conditions and visual function deterioration can affect people at any age, these most often impact older drivers as part of the aging process. In both Arizona and Florida, this appears to be most evident through the over-representation of older drivers mostly cited for at-fault traffic collisions and violations. In 2002, among the drivers with any violation, daylight conditions account for the majority of collisions in the age 55 years and older population. The cohorts age 65 years and older constitute the largest percentage of drivers who fail to yield the right of way (Williams et al., 2003). The proportionally higher number of these types of collisions in Arizona suggests that the current visual acuity testing methods for drivers may be inadequate. According to Pitts, visual acuity rapidly declines with increasing age after age 50 years. Studies by Decina and Staplin (1993) reveal the onset of this change at approximately age 45 years. This study demonstrates that an increase in at-fault collision involvement coincides with the drivers, age 50 to 59 years, in both Arizona and Florida. Drivers age 80 to 89 years primarily exhibit the highest Relative Accident Involvement Ratio (RAIR). They are most likely at-fault in collisions, compared to their younger counterparts. These values are in good agreement with those illustrating collision involvement due to visual defects.

Interestingly, some experts argue that visual acuity testing does not provide a comprehensive vision assessment when compared to contrast sensitivity testing, especially with respect to age-related macular degeneration (AMD), cataracts, or glaucoma, optic neuritis, and diabetes, (Meszaros, vol. 29). Eye charts are particularly ineffective because patients can see dark letters through the cataract. Patients may also easily memorize rows of various Snellen acuity charts. Fink and Sudan (2004) show that Snellen acuity, the most widely used vision testing measure, accounts for less than 0.1 percent of the visual field and fails to quantify contrast sensitivity and color vision, two of several visual parameters needed for safe driving. Clearly, there exists a great need for automated visual acuity testing. A fast and effective visual acuity test, such as the B1Max ™ combines high- and low- contrast visual acuity screening and offers successful deployment as demonstrated through the widespread distribution of Roadwise Review® through AAA, the largest automobile association operating nationally and internationally.

Charman (1997) discusses the challenges that countries face when setting or seeking to modify visual standards for drivers. These appear to relate directly to the difficulty of defining statistical thresholds of safe and unsafe drivers. Costs of testing and implementing new vision testing standards and other measures of driving performance, aside from vision, pose additional obstacles. While restricted licenses appear to strengthen visual standards of some drivers, others, especially dementia drivers, go unnoticed due to the inadequate vision testing processes in motor vehicle department settings.

Contrast Sensitivity

Contrast sensitivity defines the ability to detect changes in contrast through resolving gratings of different spatial frequencies at various contrast levels. Contrast sensitivity appears to characterize visual disability in patients with cataracts. It also seems to measure activities of daily living (ADL), the day-to-day ability to perform domestic tasks, in dementia patients (Cormack et al., 2000). McGwin et al. (2000) associate decreased contrast sensitivity with left turn driving difficulties. Owsley et al. (2001) link severe contrast sensitivity impairment in one eye from cataract to an increase in collision risk. It therefore seems reasonable to assume that contrast sensitivity testing merits implementation in driver’s license testing, as suggested by Decina and Staplin (1993).

Color Vision

Color vision, the ability to see and process differences in colors, and perception, the cognitive ability to discern among wavelengths of light, allow the driver to effectively and readily respond to signage and change of traffic signals. A lack of either of these abilities may prove hazardous while driving. According to Staplin (2005), research does not confirm a relationship between color deficiency and collision risk. Also, a minimum of ten minutes per computerized test may be required “….to obtain a reliable measure of color deficiency/blindness …. where the display quality (of the monitor) must be checked repeatedly to insure precise stimulus properties and a large number of trials is required to be confident of test results…”

wpe1B.gif (58082 bytes)

 

Figure 1. Horizontal section of the human eyeball and some common conditions that may affect it.

Some Diseases Of The Eyes

Age-Related Macular Degeneration

Age-related Macular Degeneration (AMD) is a progressive disease that affects straightaway, central, vision. It impacts the macular area and fovea, the tissue surrounding the central portion of the retina. (See Figure 1.) This deterioration of the macula area of the retina is called macular degeneration. AMD occurs as nonexudative (or “dry”) AMD and exudative (or “wet”) AMD. The nonexudative, atrophic, or “dry” form is most widespread and appears in nearly 90 percent of all AMD patients (Quillen, 1999). Dry AMD, while fairly damaging, rarely causes severe blindness. However, the exudative, neovascular, or “wet” form of AMD is most destructive. Irreversible impairment to the cones and rods, two types of photoreceptors responsible for the visual response to light, result when hemorrhaging, leaking fluid, or scarring of abnormal blood vessels that grow from the choroids, a layer of high vascularity located between the retina and the sclera, into the macula region occur.

Each year, approximately 200,000 people per year are inflicted with AMD (Oliwenstein, 2002). Approximately 1.47 percent of U.S. citizens at age 40 years and older, or more than 1.75 million, are affected by neovascular AMD. By 2020, this number is expected to jump by 50 percent to 2.95 million U.S. individuals. According to the Eye Diseases Prevalence Research Group (2004), AMD significantly increases with age. AMD occurs in more than 15 percent of white women age 80 years and older. Smoking appears to increase the risk of AMD by as much as 15 percent. Although it is the leading cause of severe vision loss among Americans age 65 years and older, studies show that only 30 percent of American adults are familiar with AMD (Oliwenstein, 2002). Owsley et al. (1998) has linked AMD with injurious collisions by older drivers.

Cataract

Cataract primarily accounts for low vision among white, black, and Hispanic persons. Congdon et al. (2004) estimates that 17.2 percent of all American adults age 40 years and older have cataract in either eye and 5.1 percent have pseudophakia/aphakia. Cataracts affect nearly 50 percent of the population of age 75 years and older. By 2020, the incidence of cataracts is expected to jump nearly 46.8 percent to 30.1 million Americans age 40 years and older; pseudophakia/aphakia, over 50 percent.

Since cataracts cloud the lens of the eyes, the condition impacts color perception and glare. It may also create diplopia, double vision. McCloskey et al. (1994) reports a 1.2 fold increased risk of injurious collisions among older drivers with diplopia. Surgical removal of the cataracts may correct vision and allow these at-risk drivers to continue safe driving practices. Owsley et al. (1999) report a study on Alabama driver’s licensees, ages 55 to 85 years, with and those without cataracts. Those with cataracts are 2.5 times more likely to have at-fault collision involvement in the prior five years and four times more likely to report driving difficulties. Carroll et al. (2002) evaluates the impacts of various levels of cataract-related glare on older drivers’ identification of highway signage in darkness. Fewer signs are correctly identified at all luminance levels with and without glare for subjects with significant and early cataracts.

Glaucoma

Glaucoma is a condition characterized by an elevated internal ocular pressure, an alteration of the visual field, and an optic neuropathy relating to a loss of nerve cells within the optic nerve (Hitchings, 2000). It causes severe loss of vision and peripheral vision. It fades images and reduces contrast. Early detection of glaucoma is key to intervention. This disease advances so slowly that most patients are unaware of any vision loss until progression occurs (Peli and Peli, 2002).

Glaucoma triggers blindness in an estimated 1.5 million people in India (Markandaya, et al., 2004). Glaucoma now affects 2.2 million Americans at age 40 years and older. Although it is the most common form of blindness among Hispanics, it is the fastest-growing eye disease among Hispanics age 65 years and older. It is expected to impact

3.3. million Americans by 2020 (National Eye Institute, April 12, 2004). Glaucoma is often tested through glare recovery, a test designed to measure the time it takes a patient to recover from the viewing of flashing bright lights, or glare. Early glare research (Wolf, 1960; Brancato, 1969; cited in Corso, 1981) shows that older adults require longer recovery time and increased brightness to discern objects.

McCloskey et al. (1994) has associated a 1.5 fold increased risk of injurious collision among older drivers with glaucoma. Owsley et al. (1998) has determined that glaucoma and restricted useful field of view, serve as strong and independent predictors of collision-related injuries for Alabama drivers ages 55 to 87 years. Useful field of view, measured binocularly, defines a visual information extraction area that functions in a single glance without eye or head movement (Roenker et al., 2003). This spatial area allows visual stimuli detection in a variety of situations (Roenker et al., 2000).

Hu et al. (1998) argue that glaucoma is the only medical condition that links older drivers, particularly males, with increased collision risk. Although they claim that high collision rates are not associated with commonly studied medical conditions, it is possible that a number of these medical conditions are not adequately screened in driver’s licensing bureaus. Therefore, the connections may inadvertently appear less than obvious.

The most common form of glaucoma is open-angle glaucoma, an insidious form that remains seemingly inconspicuous until severe and permanent peripheral vision is evident. This disease impacts the trabecular meshwork and optic nerve of the eye. (See Figure 1.) In children, it also disturbs the sclera (Congdon, et. al., 2003). Approximately 1.86 percent of American adults age 40 years and older are now affected with open-angle glaucoma. Open-angle glaucoma may appear in three times as many blacks than whites. By 2020, this disease is estimated to rise by 50 percent to 3.36 million American adults (Friedman et al., 2004).

Low, normal tension glaucoma occurs when normal to low ocular pressure exists. A lack of blood circulation in the eye reduces sight, causes loss of peripheral vision, and damages the optic nerve. The angle-closure glaucoma affects the anterior chamber and optic nerve of the eye.

Hemianopsia

Hemianopsia results from optic nerve degeneration. This may relate to injury, trauma, tumors, and other contributing causes that may reduce sight, contrast, photophobia, peripheral vision loss, and color vision change.

Optic Atrophy

Optic nerve degeneration defines optic atrophy that may relate to injury, trauma, tumors, and other contributing causes. This may reduce sight, contrast, photophobia, peripheral field loss, and color vision changes.

Refractive Error

Refractive error describes the inability of the eye to properly focus images on the retina. Refractive error occurs as myopia (nearsightedness, shortsight), hyperopia (farsightedness, long sighted) and astigmatism. An individual with myopia has the ability to see near objects clearly but not in the distance. An individual with hyperopia has the ability to see objects in the far distance but may not see near images clearly. Astigmatism results in a blurred image through an inability of the cornea to properly focus an image onto the retina. Contact lenses, eyeglasses, or refractive surgery often correct myopia and hyperopia.

Refractive errors primarily cause visual impairment and blindness in the developing world (Congdon et al, 2003). Kempen et al. (2004) determined that 33 percent of Americans and Western Europeans and 20 percent of Australians age 40 years and older are affected by refractive errors. Cheng et al. (2003) observed that an increase in prevalence of refractive errors, specifically myopia, astigmatism, and anisometropia, significantly increased with age in Chinese adults age 65 years and older in Taiwan. Myopia appears to be common in East Asia. Wong et al. (2000) determined that there exists an overall prevalence of refractive errors, in particular, myopia, in 38.7 percent of 2,000 Chinese residents, age 40 to 79 years, in Singapore. This rate is nearly double the rate observed in Caucasians and Blacks of similar age cohorts.

Infectious Disorders of the Eye

Various communicable diseases of the eye are prevalent in regions of destitute throughout Africa, Australia, the Middle East, and Southeast Asia. Not only do many inhabitants of these areas lack adequate medical facilities and care, if any, but also effective sewage and potable water, among other factors. As a result, poor hygiene, an agent for disease, is very widespread.

Chlamydia Trachomatis

Chlamydia trachomatis, a bacteria, causes trachoma, an eye infection, that, when left untreated, may lead to blindness or chronic scarring. Although trachoma ocurs globally, it is rarely found in the United States except in impoverished areas where poor hygiene and crowded living conditions exist. The National Institute of Health (2004) indicates that affected individuals with trachoma can transmit this disease through direct contact with eye or nose-throat secretions, contaminated objects (e.g., clothes or sheets), and through infected flies.

Onchocerciasis

Onchocerciasis, commonly called River Blindness because it occurs along rapidly flowing rivers and streams, affects 17 million people worldwide. According to the Centers for Disease Control (2004), female black flies (Simulium) transmit a disease produced by the prelarval and adult stages of nematodes, parasitic worms, Onchocera volvulus. More than 25 global nations, including the central part of Africa, host Onchocerciasis. The bite of certain species of these black flies, among other infections, can cause ocular lesions that can lead to blindness. Symptoms may not appear for months or years until after exposure.

Human Immunodeficiency Virus, HIV

Human Immunodeficiency Virus, HIV and HIV-associated infection, may lead to secondary infection, in particular, cytomegalovirus (CMV) retinitis. This infection, which may advance to blindness, if untreated, tends to affect the eyes of patients during the late stages of AIDS. Highly active antiretroviral therapy may account for the significant decrease of these incidences in the developed world since the 1980s (Congdon, 2003).

Nutritional And Metabolic Factors

Diabetic Retinopathy

Diabetic retinopathy impacts people with diabetes, a disease defined by a lack of production or use of insulin by the human body. It results in central vision loss and occurs when blood vessels leak fluid within the eyes. It affects vision through the retina and vitreous humor. (See Figure 1.) Among middle-aged Americans, diabetic retinopathy is the leading cause of new blindness (Quillen, 1999). It also results in vision loss in older populations. This disease adversely impacts night vision. Some studies suggest that this disease may contribute to collision risk in older drivers (McGwin, Jr., et al. 1999). In the developed world, diabetic retinopathy is a primary cause of blindness and visual impairment in adults less than age 40 years (Congdon, 2003). Diabetic retinopathy is prevalent in 4.1 million adult Americans age 40 years and older. As the population ages, diabetic retinopathy may eventually pose a public health threat as more people develop diabetes mellitus (DM) and face possible vision loss (Kempen et al., 2004). Diabetic retinopathy may affect 7.2 million Americans by 2020 (National Eye Institute, April 12, 2004).

Vitamin A Deficiency

Vitmain A deficiency stems from a lack of essential vitamins in a balanced diet. Patients with vitamin A deficiency may experience dim light or poor night vision (night blindness). Dietary intervention and treatment are neccesary to prevent blindness. In some developing countries, especially where malnutition is widespread and medical services are limited,Vitamin A deficiency accounts for childhood blindness.

Ocular Trauma

Trauma to the eyes often result from assaults, sports, or occupational injuries. Ocular trauma may lead to monocular blindness Nearly 500,000 blinding ocular injuries occur both globally and annually (Congdon, 2003). Ocular trauma affects any part of the eye.

Alzheimer’s Disease, Dementia, and Driving

Alzheimer’s disease, the most common primary dementia in the United States, characteristically impacts memory and visuospatial, linguistic, and executive functions (Lee, 2001). Alzheimer’s disease and dementia also pose potential problems for drivers who may not be able to see, judge, and process information as normal drivers would. Uc et al. (2004) report that drivers with mild AD are most likely to make incorrect turns, commit more navigation errors, and make more at-fault safety errors in an instrumented vehicle equipped to record and assess driver speed, steering, braking, and acceleration. Impairments in early AD include but are not limited to: object localization and recognition, reading, route finding, visual attention, and visuospatial abilities. Similarly, dementia sometimes proves hazardous to drivers who may lose their sense of time or direction. While there are various stages and varieties of dementia, it is necessary to screen drivers because conventional vision testing methods and self-screening assessments may not easily detect this condition. Drivers with dementia may not recognize the symptoms and, hence, may lack the ability to acknowledge that they have dementia and cease driving, if necessary.

Since 1980, Alzheimer’s disease has more than doubled to approximately 4.5 million Americans. By 2050, it is estimated that the incidence of Alzheimer’s disease will jump to 11.3 million to 16 million Americans (Herbert, 2003). Although rare and hereditary forms of Alzheimer’s disease may appear in the age 30s and 40s cohorts (Bird et al., 1989), the greatest risk factor is increasing age. Alzheimer’s disease appears in nearly 10 percent of all cohorts age 65 years and older and approximately 50 percent of all cohorts age 85 years and older (Evans, 1989). Pritchard et al. (2004) report that between 1979 and 1997, the incidence of dementia, primarily Alzheimer’s disease, trebled among adult (age 45 to 74 years) neurological deaths in Australia, Canada, France, Germany, Italy, Japan, Netherlands, Spain, United Kingdom, and the United States. Environmental toxins and pollutants may account for these concomitant upsurges. As long as people with dementia have a mortality rate 3.5 times higher than the general population rate (as cited in Pritchard et al., 2004), we an assume that collision risks among these drivers will also increase.

Hopkins et al. (2004) estimate that the number of dementia drivers in Ontario, Canada will increase three fold between 2000 and 2028 to approximately 100,000. Among those aged 65 years and older, the overall dementia prevalence rate is estimated at 8.7 percent in 2000. The at-risk dementia drivers are approximated to constitute only one-half of all dementia patients. Hopkins et al. urge driving policy and screening test reforms to weed out dementia drivers, especially of the Alzheimer’s type, who may continue to drive well into a disease that persists 8 to 10 years after the onset of symptoms. They note that physicians, through Section 203 of the Ontario Highway Traffic Act, are required to report patients who have medical conditions that may negatively impact their driving performances. Yet, these physicians are not trained to detect dementia drivers or other at-risk drivers.

According to the Florida At-Risk Driver Council (2004), mild to moderate dementia drivers constitute more than 20 percent of all 242,480 drivers age 85 years of age and older for the fiscal year 2002 to 2003. This leads to the question of whether a similar proportion of drivers are now on Arizona roads, since both states are characterized by similar population growth, percentages of older adult cohorts, and climate. It is possible that a number of dementia drivers may account for the high collision, injury, and fatality rates that are observed in Arizona.

Wolf (2004) notes that it is estimated that more than 500,000 drivers with Alzheimer's disease now hold Florida driver's licenses and there is no system available to screen or monitor these kinds of drivers.

Janke and Eberhard (1998) of the California Department of Motor Vehicles and the National Highway Traffic Safety Administration (NHTSA) sought to create a battery of non-driving tests and road tests to identify elderly drivers with dementia or other aging-related medical conditions. These tests were included in a pilot study and reviewed on the bases of detection of driving performance and functional impairment. By 2002, the University of Iowa Hospitals and Clinics installed driving simulators to study licensed drivers who were Alzheimer’s disease patients. It was determined that 33 percent of all of these drivers were involved in simulated collisions due to inattention or slow reaction time (Rizzo, 2002).

Although cognitive function maladies generally define degenerative dementias, there are several studies that document sensory, particularly visual, decrements in these patients. While some research fails to link visual acuity changes as gauged by the traditional Snellen eye chart, Cormack et al. (2000) cite a number of studies that relate impaired visual acuity and visual hallucinations in patients with Alzheimer’s disease. They also refer to studies that clearly document color vision, contrast sensitivity, stereoacuity, and visual acuity impairments in dementia patients. Other studies document a link between decrements in visual acuity and contrast sensitivity with Alzheimer’s disease and other dementia patients (Mendez, et al. 1990; Lakshiminarayanan, 2000; Cormack et al, 2000). Decreased visual acuity under low luminance has also been associated with dementia patients, including those with Alzheimer’s disease (Lakshiminarayanan, 2000). Yet, traditional Snellen type charts are often unable to detect Alzheimer’s disease and dementia since these tests are typically conducted in normal light conditions.

Driving simulators are therefore supplemental methods of screening these at-risk drivers because they may offer ambient weather and light conditions as part of the process of Dynamic Vision Assessment for Transportation (DVAT ™). The simulation of these conditions, all that contribute to the environmental factors as described, e.g., in the Haddon Matrix (Haddon, 1972), may ultimately improve our vision screening methods, especially of at-risk drivers and, possibly, dementia drivers. (In transportation engineering studies, the Haddon matrix serves as a framework for injury prevention identification. Events occur within a certain time sequence, as defined by the matrix.) Driving simulators may also weed out drivers with strokes and other neurological disorders, including Parkinson’s disease, a progressive, neurodegenerative disease characterized by tremor and impaired muscular coordination that affects more than 500,000 Americans (National Institute of Neurological Disorders and Stroke, 2004) and has doubled in incidence between 1979 and 1997 (Pritchard et al., 2004). Also, contrast sensitivity testing and other traditional vision testing methods of dementia patients tend to be time-consuming and challenging.

It is important to note that diagnosis of a neuropsychologic or neuromotor disorder does not imply driving impairment. However, in some cases, these diseases, especially in advanced stages, may disallow the safe operation of motor vehicles. Most physicians may not know how to identify these diseases in their patients without the use of specialized equipment or actual driving observations. Ott el al. (2005) report that a clinician’s assessment alone “….may not be adequate to determine driving competence in those with mild dementia.” Hence driving simulators may prove especially useful for such assessments, especially when the incidence of dementia is expected to jump 400% over the next twenty years (Whitmer et al., 2005).

Some Driver’s License Vision Testing Policies: An Overview

In order to better understand the vision testing processes at driver’s license bureaus in Arizona, Florida, and the United States, it is necessary to evaluate the vision testing policies in these places as well as in other countries. A number of these places are identified in our global survey (Appendix B).

Driver’s license renewal policies are a fundamental part of the vision screening program. These policies serve to weed out drivers who may cause harmful collision events. In light of recent studies by Owsley et. al at the University of Alabama in Birmingham that show, for example, how driver refresher training courses for older drivers do not reduce older driver-involved collisions (Owsley, et al., 2004), the driver’s license renewal policies provide an even greater role for promoting safety on roads.

Arizona

In Arizona, a driver’s license is valid until age 65 years. Any person age 65 years and older who renews by mail must submit a vision test verification form, provided by the Motor Vehicle Division (MVD), or certification of an applicant’s vision examination, conducted no more than 3 months earlier. Visual acuity testing is required for driver’s license renewal every 12 years until age 65 years. After age 65 years, testing is required every five years. Drivers age 70 years and older are not allowed to renew their driver’s licenses by mail.

According to Arizona Administrative Code, Title 17, section R17-4-502, 2002, in the State of Arizona, an examination is required when the license applicant indicates that a visual condition has either developed or modified “…that may constitute a disqualifying medical condition.” This, however, only considers the driver who discloses a visual disorder, among other possible conditions. Many drivers, especially dementia drivers, are unaware of these possible visual disorders and, therefore, continue to drive without adequate assessments.

Florida

For a number of years, Florida law permitted drivers at any age to go without vision testing for as long as 18 years (Clark and Kripalani, 2003). In January 2004, a law was enacted in Florida to require drivers age 80 years and older to submit to a vision test at either driver’s license bureaus or licensed physicians. Test results are now required for renewal. Alternative means of transportation, public awareness, and safer approaches to allowing older drivers to remain on the road are also vigorously pursued.

Field of vision measurements are only used in the State of Florida when submitted by ophthalmologists or optometrists.

United States

In the United States, driver’s license application and renewal procedures vary from state to state. There may be age-based assessments (medical, road, vision, and/ or written tests) and frequencies of renewal periods. There may also be requirements for in-person, computer-based, or post mail renewals.

Several studies point to a lack of uniform vision screening standards and testing in the United States (Demers-Turco, 1996; Peli and Peli, 2002). Each state motor vehicle bureau operates independently. According to Decina et. al (1997) vision screening apparatus availability, ease of test administration, and medical opinion consensus generally govern the current U.S. vision standards and testing methods. The impetus to modify vision testing methods stems from years of survey and research, most recently through several studies commissioned by the NHTSA (Staplin et al., 2003a, 2003b, 2003c). A survey by the American Association of Motor Vehicle Administrators (AAMVA) and the National Highway Safety Administration (NHTSA), “AAMVA/NHTSA Survey of States/Provinces on Model Driver Screening/ Evaluation Program”, reveals that eighty-five percent respond favorably to possible modifications incorporating dynamic visual acuity, contrast sensitivity, and low luminance acuity (Staplin et al., 2003a).

Only 26 percent of all U.S. states require frequent vision testing for older drivers through shorter license renewal periods or in-person renewals. These include Arizona, California, Colorado, Florida, Hawaii, Idaho, Indiana, Iowa, Kansas, Missouri, New Mexico, and Rhode Island. Driver reexamination is prohibited on the basis of age in Maryland, Minnesota, and Nevada. Ageism with respect to driver’s licensure is against the law in Massachusetts. Shipp et al. (2000) support comprehensive vision testing for at-risk drivers at driver’s license renewal.

Approximately half the U.S. drivers age 85 years and older do not meet motor vehicle bureau vision standards (Susman, 1999). This is a great concern, along with the increasing lack of health insurance in the United States. While laws require drivers to possess driving insurance, and most U.S. states require motorists to possess liability insurance for vehicle registration or rental purposes, personal health insurance coverage is optional. In 2003, approximately 15 percent, or 43 million, of the U.S. population was uninsured. These people, of all ages, lacked private, public, government, state, or military health insurance plans, among other possible types of coverage. This value is slightly higher than the 14 percent of the population estimated to lack health insurance coverage in 2001 (U.S. Department of Health and Human Services, 2004). Yet, the American Public Health Association (2004) reports that in some or all of the years 2002 to 2003 more than 80 million Americans lacked health insurance. The states of Arizona and Florida are ranked among the highest rates of uninsured in the U.S. because nearly one out of every three of the total population under age 65 years in these states were uninsured during this time period.

Consequently, millions of American drivers may not have access to regular or periodic vision examinations in a medical setting. McCloskey et al. (1994) suggest that for insured Americans, optometrists do not routinely administer sophisticated vision tests that may identify high-risk older drivers. In Oregon, effective June 1, 2004, a Medically At-Risk Driver Program requires a mandatory medical reporting process (through certain physicians and health care providers) of persons age 14 years and older who have severe and uncontrollable functional and/or cognitive impairments that are likely to impact the person’s ability to safely operate a motor vehicle. However, Oregon House Bill 3071, while helpful for the drivers who carry health insurance, does not seem to address drivers who lack it. This law also functions on the premise that the physicians and health care providers are adequately equipped and/or trained to assess drivers for these functional and/or cognitive impairments, particularly those that adversely impact vision.

Therefore, millions of drivers on our roads may not have been screened for eye disease or impairment. These drivers may not have access to regular or periodic vision examinations in a medical setting. The onus then falls onto the state driver’s license bureaus to adequately screen all drivers, including the uninsured, for visual impairments.

A recent survey commissioned by the DOT indicates that 63 percent of the AAMVA member respondents support the privatization of some driver’s license qualification assessments (Staplin et al., 2003a). However, these activities are not explicitly defined. One cost-effective strategy devised to alleviate this burden of responsibility on all driver’s license bureaus is the possible completion of all vision testing and certifications through driver insurance programs (Semmens, 2004). This way, vision tests could be conducted at each annual motor vehicle insurance renewal period and, via a computer network, presented to driver’s license bureaus through an on-line program to reduce paperwork and additional staffing concerns. Queues would also be shortened due to the numerous vision testing offices and satellite locations.

A number of studies address collision risk and driver’s license renewal policies. Overall, the link appears to be weak due to inadequate vision testing mechanisms and the dire need to improve these methods and obtain empirical data to institute new vision test processes at all driver’s license bureaus. Shipp et al. (2000) note the limitations associated with existing vision tests as a means of screening functional visual impairments. They also support status quo maintenance, mandatory vision testing for driver’s license renewal, uniform and stringent vision screening requirements, comprehensive eye examinations by ophthalmologists or optometrists, and mandatory vision testing for initial and renewing driver’s license applicants as ways of addressing the projected increase in at-risk visually impaired drivers in all U.S. states.

Levy et al. (1995) associates lower collision-related fatality risks of drivers aged 70 years and older with state-mandated visual acuity tests and U.S. driver’s license renewal policies. Dobbs et al. (1998) shows that driver’s license removal criteria are ineffective in North America on the bases of a road driving study and the identification of clinically-impaired older drivers through hazardous error associated with driving, positioning, and turning of motor vehicles. Shipp (1999) demonstrates that several factors, including a lack of a vision test at license renewal and a high population density escalate the likelihood of older driver fatalities. Rock (1997) does not associate collision, licensure, or fatality rates of older Illinois drivers, from years 1987 to 1989, and 1995, with accelerated renewal periods for older drivers and road test removals for drivers under age 75 years. According to Owsley et al. (2003), collision risks increase among visually impaired older drivers who satisfy the legal licensing requirements. On the basis of years 1990 to 2000 U.S. data, Grabowski et al. (2004) does not associate frequent license renewal, in-person renewal, state-mandated vision, and road tests with fatality rates among drivers age 65 to 74 years and 75 to 84 years. However, lower fatality rates are linked with in-person license renewal among the older drivers.

Furthermore, Rock (1997) discusses the impacts of sweeping reforms on collisions, fatalities, collision rates, and licensure rates in Illinois older drivers’ license renewal requirements. The changes include road test elimination for ages 69 to 74 years and reduction in length of license terms and renewal requirements (from four to two years) for ages 81 to 86 years and one year for ages 87 years and older. No benefits are reported through these changes, including the administration of vision tests at driver’s license renewal. These results may be expected when the testing methods are ineffective and unchanged.

Australia

By 2051, the proportion of adults age 65 years and older is expected to reach 24.2 percent in Australia (Langford et al., 2004). Researchers and driver’s license officials have taken a very proactive role in developing new standards and assessment methods to adequately screen at-risk and older drivers throughout Australia. Some of these results have been reported by Fidles (1997), Fildes et al. (2001), Charlton et al. (2001), Andrea et al. (2002), Langford et al.( 2004), among others.

Fildes (1997) reports that by the late 1990s, age requirements for license renewals existed in nearly 75 percent of Australia except for Northern Territory and Victoria. Fildes also notes that annual vision tests, for all ages, were required in approximately 50 percent of Australia, including Australian Capital Territory, New South Wales, South Australia, Tasmania, and Western Australia. Interestingly, in Western Australia, as of 2000, regulations require licensed drivers at 75, 78, and 80 years, and every year to 84 to have an eyesight test and medical form completed by a doctor. Licensed drivers at age 85 years and every year after are required to complete a practical driving assessment in addition to the completion of an eyesight test and medical form (The Government of Western Australia, Road Safety Council, 2000). In South Australia, an annual medical assessment is required for drivers aged over 70 years to retain their license. Although annual driving tests are not required, referrals are sometimes issued according to a physician’s discretion (Hunt, 2005).

Keeffe et al. (2002) reveal that while older drivers tend to refrain from or limit their driving, many visually impaired drivers remain on the roads in Australia. Although it is demonstrated that no difference in likelihood for collision exists between people with good vision than those with visual acuity less than 20/40 (6/12), it is estimated that only

2.6 percent have vision less than that required for driver’s licensure. This study supports the need for improved vision testing, standards, and policy in Australia.

In 2003, the parliamentary Road Safety Committee of Victoria, Australia released a report with several recommendations for older drivers. Those included compulsory license renewal vision testing, routine medical evaluations, mandatory medical testing for licensing drivers age 80 years and over, and the shortening of the license renewal period from 10 to 5 years for drivers age 65 years and older, among other recommendations. Victoria is the only state in Australia that offers vision testing only to driver’s license applicants. All other states provide vision testing at the driver’s license renewals (Lennon and Leunig, 2003).

Langford et al. (2004) evaluate various older driver’s licensing procedures through older driver fatal and serious injury collision involvement rates across all Australian states. They report that Victoria lacks a mandatory driver assessment program yet has the lowest older driver collision rate per number of driver’s licenses issued. Hence they conclude that older driver safety benefits do not appear to be linked to various age-based mandatory assessment procedures. As this report demonstrates, however, there are many collision factors, apart from the denominators of per population and per number of licensed drivers issued that require extensive review and analysis. These may include but are not limited to the same RAIR analyses we conducted in our report.

Additionally, some recent studies do not link collision rate with driver’s license vision testing practices (Hull, 1991). Clearly, this may be attributed to the ineffectiveness and inadequacy of these testing methods not only in Australia, but other countries as well. For example, our research shows (Appendix B, Table 2) that 75 percent of Australian states solely utilize

Snellen-type eye charts as a means of visual acuity and vision testing of drivers. Fink and Sadun (2004) show that the most common measurement of ranges of vision loss (International Council of Ophthalmology, 2002), visual acuity, defines less than 0.1 percent of the visual field. Failure to measure contrast sensitivity in driver’s license vision tests directly and adversely impacts driver safety.

Not only are new national and international comprehensive vision measurement standards needed, but also improved vision testing methods. Once these changes are in effect, we may observe a stronger link between driver’s license vision testing, initial and renewal driver’s license procedures, and types and rates of collisions and collision involvement across Australia and elsewhere.

United Kingdom

In the United Kingdom, it is estimated that the cohorts age 60 years and older constitute 20 percent of the population. By 2031, they will form 30 percent of the population (United Kingdom Department of Transport, 2002). Meanwhile, these older drivers are two to five times more likely to die or suffer serious injury in any collision due to increased frailty (Holland, et al., 2003).

Since 1935, the basic U.K. visual requirement for driver’s license applicants remains the number plate test, which involves reading in daylight a number plate with symbols three inches (79.4 mm) high at a distance of 67 feet (20.5 m), with or without corrected lenses, at a nominal binocular Snellen acuity of approximately 6/15 in meters or 20/50 in English units. Self-declaration of the ability to pass is required on all driver’s license applications and verified at driving test time. No additional tests are required until age 70 years yet over the years, the U.K. visual standards have been deemed inadequate due to seemingly higher vision test standards in many other countries and suggestions that many current drivers could not pass the U.K. number-plate test. Contrastingly, Davison and Irving (1980) report that possible age-related visual acuity decrements appear in drivers as early ages 40 to 44 years when they fail to achieve mean U.K. Snellen acuity levels. Such findings seem to support studies in the United States by Decina and Staplin (1993) that reveal the onset of this change at approximately age 45 years. Others have expressed concerns about the lighting conditions, lack of standardization, symbol design, etc. Meanwhile, younger drivers appear to contribute most to collisions in the United Kingdom. Misinterpretation of road signs may account for the disproportionate number of maneuvering errors among older drivers (Charman, 1997).

Although many concerns remain about the U.K. driver’s license requirements, Charman (1997), whose study was commissioned by the United Kingdom Department of Transport (DfT), does not recommend changes in current driver’s license requirements due to the lack of a single test or combination of tests to effectively screen at-risk drivers without disqualification of safe drivers. However, Currie et al. (2000) challenge the effectiveness of the Snellen acuity chart and, on the bases of analyses of patients and questionnaires to health care professionals, deem it a poor predictor of one’s ability to meet the required driving visual standard in the United Kingdom. These findings appear to be supported by Schneck et al. (2002), especially as they relate to older drive, contrast sensitivity, and low luminance conditions.

Unsurprisingly, most medical and health care professionals lack the time, resources, and training to provide any more than basic screening to assess an unwell or medicated driver’s fitness to drive. In the United Kingdom, many doctors are not familiar with laws governing assessment of drivers. The burden of responsibility lies primarily on the driver and the Driver Vehicle Licensing Authority (DVLA) to determine whether a patient is fit to drive (Holland et al., 2003). License review for fitness to drive is required at age 70 years, and subsequent frequency of license review is every 3 years. A minimum horizontal field of 120 degrees is required by the European Union Directive and recommended in the United Kingdom (Charman, 1997).

Interestingly, according to the DfT (1995), Australia, Canada, New Zealand, and the United States all have higher fatality rates per 100,000 population than the United Kingdom.

New Zealand

In New Zealand, older drivers at ages 75, 80 and every two years thereafter are currently required to renew their driver’s licenses. While medical certification is a requirement for these drivers, an on-road driving test is also compulsory from age 80 and every two years thereafter. An eyesight examination or certificate is required for license renewals.

Canada

An overview of the testing policies of Ontario is presented. The reader is referred to Canadian Ophthalmological Society, specifically for recommendations on vision standards for driving in Canada. Ontario requires at-fault drivers age 70 years and older to take a vision test, a general knowledge test and a road test. The age 80 years and older drivers are required to take a vision test and a general knowledge test, in addition to a skills refresher course every two years (Lazaruk, 2004). Hopkin et al. (2004) indicate that the road test component was likely removed for these cohorts due to increases in associated expenses and numbers of drivers age 80 years and older. The screening process also appears to be inadequate because it can neither detect dementia drivers nor drivers in the early stages of dementia. Hence other at-risk drivers are also ineffectively screened.

The number of Ontario drivers age 65 years and older are estimated to increase fivefold in the 42-year period between 1986 and 2028, to approximately 2.5 million drivers. Drivers age 80 years and older constitute the fastest growing age group of drivers in Ontario. In just 10 years, the number of Ontario drivers age 80 years and older jumped 152 percent to 115,709 drivers in 1997. Tasca et al. (2000) report that collision risk is higher among drivers age 80 years and older compared to drivers age 70 to 79 years cohorts in Ontario, Canada. Hence Canada, and in particular Ontario, face many of the same challenges as Arizona and many other U.S. states and other countries (Hopkins et al., 2004).

Vision Testing: Self Versus Other

Self-assessment of visual impairments is risky because some drivers may not wish to reveal their medical limitations or may not be aware of their visual impairments. Nevertheless, road safety is compromised. Ball (2003) reports that questionnaire research reveals that standard clinical measures do not adequately identify visual difficulties in older adults and that “…. older adults are sometimes totally unaware of their visual problems.”

Ideally, licensed medical officials should administer comprehensive vision testing on-site at driver’s license bureaus. Since this would prove to be a very costly endeavor for most, if not all, driver’s license bureaus, then an effective on-site vision testing exam or process is needed to discourage bias and to promote driver safety. Annual comprehensive eye examinations are crucial for eye disease prevention or detection.

It is possible that no one has been able to demonstrate a strong link between visual acuity and collision risk because of the following:

·       Visual acuity scores are not comprehensive assessments of driver vision.

·       The lack of empirical data governing the effectiveness of driver’s license bureau vision testing machines precludes other possible inferences.

Burg conducted one of the earliest large-scale studies involving vision screening methodology in 1968. On the basis of 3-year driving records, visual performance, and other characteristics of a sample size of n>17,000 California driver’s license applicants, he determined that driving accidents and convictions were most closely associated with dynamic visual acuity, static acuity, field of view, and glare recovery.

Field Of Vision Testing

The visual field measures the ability to see objects at a distance. It quantifies peripheral vision, commonly referred to as side vision, the visual processing of objects and movements outside of the direct line of vision. Most U.S. states require a visual field of 100 degrees or more, along the horizontal dimension for driving (Peli and Peli, 2002). Others require decipheral vision testing for commercial drivers.

According to McCarthy (2004), 62 percent of the U.S. states test a driver’s license applicant’s field of vision in addition to visual acuity. These states include Arkansas, California, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Kansas, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Nebraska, Nevada, New Hampshire, New Mexico, New York, North Carolina, North Dakota, Ohio, Oregon, South Carolina, South Dakota, Virginia, Washington, Wisconsin, and Wyoming. However, only 26 percent of all U.S. states require frequent vision testing for elder drivers through shorter license renewal periods or in-person renewals. These include Arizona, California, Colorado, Florida, Hawaii, Idaho, Indiana, Iowa, Kansas, Missouri, New Mexico, and Rhode Island. Driver reexamination is prohibited on the basis of age in Maryland, Minnesota, and Nevada. Ageism with respect to driver’s licensure is against the law in Massachusetts.

Again, these field of vision tests, while necessary, are neither comprehensive nor automated.

Older Versus Younger Drivers

Fragility and injury susceptibility, account for the disproportionate number of older drivers killed in motor vehicle collisions (Li, et al., 2003). Cognitive, motor, sensory, and visual abilities also weaken due to age-related processes and diseases. Cognitive skills, sensory and motor capabilities, and reaction time tend to decrease as driver age increases. Hence there are susceptibilities to collisions due to physical impairments, medication usage, and perceptual lapses. Medication can impair visual and driving performance. While young drivers may have a greater involvement in collisions associated with alcohol and narcotics, older drivers, especially the elderly, are more likely to be involved in medication-related collisions than their younger counterparts. These perceptual lapses include, but are not limited to failures to acknowledge signs or signals or to yield the right of way. These factors tend to contribute to a rise in injury-related collisions and left-turn collisions. Wood (1994) suggests that older drivers may experience difficulty performing simultaneous tasks due to increases in reaction times, psychomotor slowing, and cognition changes associated with attention and recognition, in addition to reduced visual performance. Visual performance decrements are associated with age (Shipp et al., 2000). Many older drivers suffer with other possible age-related ailments, including arthritis. These can affect neck and arm movement. In addition to visual problems, these ailments could pose safety problems for drivers, especially when experiencing blind spots. The potential for incidents involving blind spots always exists when driving, particularly when changing lanes. A number of interesting studies describe the differences between older and younger drivers with respect to collision risks. Others define PRT, Perception Response Time, and gauge driver performance by measuring the length of time between the appearance of a threat in the driver’s field of view and the start of braking. PRT is often used to quantify older driver performance.

According to Evans (1998), a significant number of fatalities include very young and very old unlicensed drivers. Many older drivers continue to drive even when their licenses are revoked. Evans also determined, on the basis of collision rate involvement, that very old U.S. drivers face an increased fatality risk. Licensing a 20-year-old appeared to pose a greater risk to motorists than licensing older drivers up to age 80 years.

Dobbs et al. (1998) cited several studies that report that drivers 16 to 24 years have higher collision rates than drivers 75 years and older. Ryan et al. (1998) determined that among Western Australian drivers, collision involvement was as high for the age 75 years and older cohorts as for the age 25 years and younger cohorts. Stutts et al. (1998) examined data from 3,238 North Carolina driver’s license renewal-seeking applicants age 65 years and older and linked cognitive test performance with crash risk. Cook et al. (2000) determined that Utah drivers age 70 years and older were more than twice as likely to have a crash involving a left- hand turn and more than likely to be killed than Utah drivers between the ages of 30 and 39 years. McGwin Jr et al. (2000) determined that decreased visual acuity and contrast sensitivity among drivers between 55 and 85 years of age accounted for high risk driving conditions.

According to Margolis et al. (2002), there is a considerable increase in motor vehicle collision and fatality rates per mile driven for drivers age 75 years and older. Claret et al. (2003) examined all 220,284 collisions between vehicles with four or more wheels in Spain during the period from 1990 to 1999 and found that male drivers age of 74 years and over posed the greatest risk of causing collisions. The onset of this trend was most noticeable for drivers after the age of 50 years. In the age 55 years and older U.S. cohorts, motor vehicle collision was identified as the second leading cause of death due to injury (University of Alabama-Birmingham Department of Ophthalmology Driving Assessment Clinic. 2003).

Medications for heart disease, stroke, arthritis, among other ailments, are identified with at-fault Alabama drivers aged 65 years and older who were involved in collisions. (McGwin Jr, 2000) Medication, clearly, can also affect the vision, motor, and cognitive abilities of drivers. Mortimer and Fell (1989) report that U.S. drivers, in 1983, age 65 years and older were involved in more fatal collisions at night than the drivers age 25 to 65 years and fewer collisions than the drivers under age 25 years. At-risk Alabama drivers, age 55 years and older, are associated with useful-field-of-view size constriction, visual sensory impairment, and/or cognitive weakening (Owsley, 1994). Owsley et al. (1998) reports that when useful field of view is reduced 40 percent or more in older drivers, they are 20-times more susceptible to injurious collisions. Several studies link collision involvement with useful field of view (Goode et al., 1998, Owsley et al, 1998).

Older drivers are more inclined to collisions associated with, among other factors, approaching traffic, failure to yield, left turns, inattention, intersections, and stop signage (Planek and Fowler, 1971, Keltner and Johnston, 1987; McGwin and Brown, 1999, Zhang et al., 2000). Wallace and Eberhard (1995) call for revisions to driver’s license renewal procedures and testing for older drivers on the basis of increased motor vehicle collision risks among drivers age 68 years and older after a study in a rural community in Iowa, from 1985 to 1989. Zhang et al. (2000) provide an analysis of collision–related factors involving drivers age 65 years and older between 1988 and 1993 in Ontario, Canada. Some increased risks of fatalities and injuries are associated with failing to yield right-of-way, disobeying traffic signs, snowy weather, and medical/physical conditions, especially for drivers age 75 years and older. Snowy weather increases fatal-injury collision risk by 60 percent for drivers age 65 years and older.

Baggett (2003) found that, when compared to younger drivers, older Arizona drivers tend to have more angle collisions, left-turn collisions, and accident involvements during daylight hours. Griffin III (2004) sought to link fragility, illness, left turns, and perceptual lapses to driver age. He analyzed Texas collision data over a 25-year period and linked older drivers with fragility, illness impairment, perceptual lapses, and left turn collisions. He determined that fragility, particularly for the cohorts age 85 years and older, tends to result in 3.72 times as many crash-related deaths as the 55 to 64 year old groups.

Matthias et al. (1996) determined on the basis of data for years 1984 to 1988 that Arizona drivers age 70 years and older were nearly twice as likely to be cited for improper turning as all other drivers combined. For Arizona drivers age 65 years and over, left-turn collisions constitute a significantly larger proportion of total collisions than for any other age cohorts. These findings are consistent with Staplin et al. (1997). Their focus group discussions with older drivers revealed that left turn maneuverability was the most challenging aspect of driving-related complexities at intersections.

A recent study conducted by Dr. Matthew Baldock at the University of Adelaide reports that the number of collisions among older drivers was lower than younger drivers in South Australia because the older drivers tend to avoid driving in rain, darkness and heavy traffic, among other adverse conditions (Hunt, 2005).

Although most driver’s licenses are renewed every eight years in Wisconsin, recent state legislation, such as 2005 Assembly Bill 43, includes a proposal for a law to require a vision test that is passed every three years for drivers ages 75 to 84 years. Drivers age 85 years and over would be required to pass vision and traffic-knowledge tests every two years. Vision tests may be administered through optometrists, ophthalmologists, physicians, and local Department of Motor Vehicle sites. According to a recent amendment to this proposal, a restricted license, with consideration of distance, routes, and time of day, may be issued to some older drivers through the Department of Motor Vehicles.

Meanwhile, there is a growing movement in New Zealand, led by Grey Power. This independent organization operates to protect the rights of people age 50 years and older and to eliminate “humiliation and stress” that older drivers, especially drivers age 80 years and over allege to face through driver’s license testing (Stuff, 2004). Recent proposals call for an end to the controversial practice of driver testing of drivers over age 80 years in lieu of a family group conference (Cousins, 2005).

In New Zealand, according to the Land Transport NZ (2002), both community referrals and computer-based tools were being reviewed as possible means to assess older drivers. Another form of further assessment, such as a practical driving test or medical examination, was considered for older drivers who failed a screening test, or who failed an assessment.

As of April 2005, legislation has been proposed by the government of New Zealand to abolish the age-based on-road driving tests. However, an optional on-road test, in certain circumstances, has also been proposed. The Driver Licence Amendment Rule is expected to be signed and implemented in early 2006. One proposal includes the establishment of a new conditional older driver license that would permit older drivers the option of obtaining either a full license (for travel in and out of a local area) or a conditional license (for local area travel only). An easier on-road test may accompany conditional licenses. Another proposal allows older drivers 80 years and over to operate either an automatic or a manual vehicle, as opposed to an automatic vehicle only.

Similarly, many U.S. state driver’s license bureaus, senators, and legislators, seek to modify driver’s license policy and renewal procedures, amid charges of ageism, especially among older drivers. Alternative transportation methods are encouraged and, through federal and state grants, some forms of public transportation and subsidized cabs are promoted. Some insurance companies, special interest groups, and medical officials offer special driver education programs and driver insurance discount incentives to assist senior drivers with self-assessment tools to determine whether they should continue driving. However, these strategies, while praiseworthy, are insufficient because, on the bases of our studies, current driver’s license testing and vision screening mechanisms are both inadequate and infrequent. For example, while Wisconsin Assembly Bill 43 appears laudable, it appears to assume that current vision testing methods are strong measures of driving ability. It also does not include proposals for screening the vision and neuropsychomotor competence of drivers of other ages, especially due to concerns associated with dementia, Alzheimer’s disease, among others. These proposals seem to target older drivers and do not account for drivers in other age groups. New Zealand, like the USA and other countries, illustrates a U-shape distribution with respect to collision-related injuries and distance driven. Dementia, although primarily associated with older people, occurs in people of all ages, particularly the middle-aged. In the United Kingdom, recent estimates show that at least 20,000 middle aged people with dementia require special support (Whalley, 2003). Yet, no new and effective methods of screening drivers, irrespective of age, in particular for vision and neuropsychomotor conditions (i.e., dementia), appear to be proposed or implememented.

SURVEY OF DRIVER’S LICENSE BUREAU DIRECTORS OR THEIR REPRESENTATIVES

As part of our project to determine if the current vision testing practices in the State of Arizona require enhancement, a comprehensive survey on the visual acuity testing methods of drivers was developed. Questionnaires were faxed or e-mailed to the directors of all driving licensing agencies of all 50 U.S. states, Commonwealth of Puerto Rico, Canada, New Zealand, the United Kingdom, and Australia from January 28 to April 16, 2004. Some officials were telephoned for follow-up interviews. We received responses from 100 percent of all national and international driver’s license bureau directors or their representatives. Our aim was to review and learn about the policies and practices of other driver’s licenses bureaus within the United States and overseas in order to provide a recommendation on a suitable comprehensive automated driver’s license testing system to ADOT. The results of this survey are presented in Appendix B of this report.

Our visual acuity survey covers all 50 U.S. states and the Commonwealth of Puerto Rico, all 10 provinces and 3 territories of Canada, all of New Zealand, all of the United Kingdom, and the 6 states and 2 territories of Australia. The provinces of Canada include Newfoundland and Labrador, Nova Scotia, Prince Edward Island, New Brunswick, Québec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia. The territories of Canada include Nunavut, Yukon, and Northwest Territories. Nunavut constitutes nearly one-fifth of Canada’s land mass yet has the smallest population. Approximately 85 percent of the 28,000 residents of Nunavut are Inuit, an indigenous people formerly called Eskimos. The states of Australia include New South Wales, Queensland, South Australia, Victoria, Tasmania, and Western Australia; the territories, Australian Capital Territory and Northern Territory.

ANALYSIS OF COLLISION DATA

Introduction

Consequences from traffic collisions include injuries, fatalities, and/or property damage. In order to ultimately design an all-new pre-pilot vision test for ADOT, it is necessary to consider the histories, modes, and trends of collisions between states. In this study, the states of Arizona and Florida are selected. In addition to descriptive statistics, risks for undesired events are estimated using some very basic risk concepts and risk analyses through statistical data we obtained through ADOT Motor Vehicle Crash Statistics Unit, Traffic Records Section, ADOT Motor Vehicle Division, and Florida Department of Highway Safety and Motor Vehicles.

Methodology

The trends and risks of the drivers of the states of Arizona and Florida are gauged with data from the Accident Location Identification and Surveillance System (ALISS) of Arizona and the Florida Highway Safety and Motor Vehicle Department of Florida databases. The data stem from the Arizona Traffic Accident Report and Florida Long Form Traffic Crash Reports provided by law enforcement agents in both states. All data are processed through special coding and programming developed by ESRA Consulting Corporation in Matlab 6.0, Release 13. All tables are produced in Microsoft Excel; all statistical figures, Matlab.

Where values are calculated based on the number of licensed drivers (hereafter referred to as “licensees”) in the states of Arizona and Florida, linear regression techniques are used to obtain the numbers of licensed drivers in the State of Arizona for years 1991 to 1996. In most exercises, we eliminate 15-year-old drivers from these analyses and calculations due to the Graduated Driver’s license Program that took effect in Arizona in 1996.

The Framework

The Haddon Matrix provides us with an epidemiological framework for injury assessments through environmental, human, and vehicular factors (Haddon, 1972). This allows us to ultimately define the likelihood and significance of injuries, for example.

Table 1. The Haddon Matrix (Songer, T., 2004).

 

HUMAN

VEHICLE

ENVIRONMENT

PRE-EVENT

 

 

 

EVENT

 

 

 

POST-EVENT

 

 

 

We can evaluate a collision sequence through pre-collision, collision, and post-collision events. However, in our study, we are primarily interested in the pre-collision event and how it relates to driving or human factors and the environment. Vehicle maintenance, failure, design, speed, and illumination all influence the vehicle factor. The driving or human factor includes age, alcohol, fatigue, gender, driving experience, training, legislation, and penalties. Road, traffic, and weather conditions constitute environmental factors (Rodrigue et al., 2004; Songer, 2004).

Rodrigue et al. (2004) indicate that direct observation, induced measurements, and survey techniques are the three widely accepted modes of exposure data collection. Exposure, a scale factor, defines the quantity of collisions in the numerator of a ratio. It simplifies the process of comparing data from two states by eliminating variables such as size and motor vehicle mileage.

Thorpe (1964) pioneered the induced exposure method to allow for a variety of risk comparisons. This led to calculations of Relative Accident Involvement Ratio (RAIR), refined by Stamatiadis and Deacon (1997), whereby each motor vehicle collision consists of an at-fault (responsible) driver and not-at-fault (not responsible) driver.

 

COMPARISON OF RELATIVE ACCIDENT INVOLVEMENT RATIO (RAIR) OF COLLISIONS OF ARIZONA AND FLORIDA DRIVERS, YEARS 1991 TO 2001

In the year 2000, 76 percent of all traffic fatalities involving older drivers included another vehicle (U.S. DOT, 2000.) The propensity of these fatal collisions, and many others that transcend driver age, reinforces the need to evaluate, among other factors, the impact of roadway lighting and other features of driver vision, perception, and performance. When these collisions occur at night, they may be attributable to a driver’s inability to notice delineation, warnings, and other possible road safety controls. Night severely restricts driver’s visual range to about 262 feet (80 meters) and impacts a driver’s ability to discern details and steadily react to stimuli (Hollnagel and Källhammer, 2003). Adverse weather conditions affect pavement markings. At night, any quantity of ice, snow, or water can cause pavement markings to appear nearly indiscernible. Interestingly, however, dry pavement accounts for 81 percent of fatalities during both day and night times (Opiela et al., 2003). As a result of this growing interest in at-fault collision involvement studies, and its underlying causes, the calculations and applications of the Relative Accident Involvement Ratio (RAIR) are presented. In order to achieve a representative sample of drivers from both Arizona and Florida, nine age groups are selected: 16 to 19 years, 20 to 29 years, 30 to 39 years, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, 80 to 89 years, and 90 years and older.

RAIR measures the likelihood of involvement in a collision. It is a ratio of the number of at-fault drivers of a certain age group divided by the total number of at-fault drivers to the number of not-at-fault drivers of a certain age group divided by the total number of not-at-fault drivers. RAIR stems from the pioneering work of Thorpe (1967) and Carr (1970). Its applications are valuable in many transportation engineering studies and analyses. Stamatiadis and Deacon (1995) utilized RAIR to study collision-related trends among drivers on the bases of age cohorts and gender.

According to Stamatiadis and Deacon (1995), accident propensity, a term used to describe RAIR calculations, is sometimes applied to measures of the ratio of accident involvement quantity to the miles of travel. Since these tend to lack accuracy because of the need for exogenous travel estimates, the RAIR approach seems most practical when direct exposure estimates are unfeasible or lacking.

As shown by Chandraratna et al. (2002), we define RAIR as follows:

wpe1D.gif (12484 bytes)

RAIR values greater than 1.0 denote a driver group more likely to be at-fault in motor vehicle collisions. RAIR values less than 1.0 designate a driver group that is less likely to be at-fault (Robertson and Aultman-Hall, 2001).

Over (1998) addresses the possibility that the classification scheme of at-fault and no-fault drivers may be open to gender bias. He also encourages the indication of the type of collision because some drivers are more susceptible to severe consequences than others.

In order to compare millions of collisions involving Arizona and Florida drivers during the years 1991 to 2001, data were compiled in Microsoft Excel format. Programs in Matlab 6.0, Version 13 were developed and ran to divide and analyze at-fault and no-fault drivers in each type of collision and state. The literature was reviewed on at-fault driver calculations and predictions.

Interestingly, Robertson and Aultman-Hall (2001) used RAIR to quantify the effects of dry, wet, and snowy/slushy roads on Kentucky drivers age 65 years and older who were involved in collisions. They determined that these drivers, when compared to drivers younger than age 65 years, were more likely to be at-fault when roads were dry. Wood and Troutbeck (1992) found possible connections between reduced contrast sensitivity and at-fault motor vehicle collisions.

However, Owsley and Ball (1993) determined a correlation between Useful Field of View (UFOV), the visual information extraction area that functions in a single glance without eye or head movement, and at-fault motor vehicle collisions. A study of drivers in Vancouver, British Columbia in 1986 indicated more at-fault automobile collision involvement among drivers age 55 years and older than drivers age 36 to 50 years (Cooper, 1990). In Germany, while accident involvement of drivers age 65 years andolder is low, the percentage of at-fault drivers is high. In 1989, however, drivers age 70 years and older represented the largest percentage (71.3 percent) of at-fault drivers as compared to drivers under age 30 years at 56.7 percent (Schlag, 1993).

Bathtub Curves

Bathtub curves are usually associated with product failure and reliability engineering. These curves illustrate an expected failure rate of, for example, an electronic component, with respect to time. Three regions define the bathtub curves: Early Failure Period (sometimes called the Infant Mortality Period, the High Initial Failure Rate, or the Burn-in Failure), Intrinsic Failure Period (also referred to as the Stable Failure Period) and Intrinsic Failure Rate, or Useful Life Period, and the Wear-out Failure Period. The Useful Life Period is sometimes called the Chance Failure or Random because it exhibits random failures of the product.

wpe1F.gif (12183 bytes)       Figure 2. The Bathtub Curve

The failure probability density function illustrates the type of behavior shown in a bathtub curve:

f(t)= bθ(θtt)b-1exp [-(e(θb) b -θtb – 1)] for b> 0, θ> 0, t > 0

where:

b = shape parameter,

t= time,

and θ= scale parameter

R(t), the component reliability function, as an approximate fit, is defined as:

R(t)= exp [-(e(θt)b – 1)]

h(t), Hazard rate, which explains probability of failure changes over the lifetime of the component (Modarres, et al. 1999), is represented by:

h(t) =    f(t)/ R(t)     = bθ(θtt)b-1e(θt) b

Interestingly, many of our RAIR graphs 30 to 43, Appendix G, appear in the shape of bathtub curves up until the age 80 to 89 years cohorts, where the Wearout Period tends to end and retirement, in most cases, begins. This may be expected because older drivers are most vulnerable to collision-related injury or death due to frailty associated with older age. Similarly, fatigue causes deterioration of mechanical and electrical components and susceptibility to external stresses. Design or defects of a product sometimes contributes to brittle behavior of a material. Therefore, in order to maximize safety of both people and products, it is necessary to seek to minimize these stress factors. In traffic-related collisions, these may be due to visual, cognitive, or motor impairments, or any combination thereof, of the drivers. Through improvements to driver’s license testing methods, we may have an edge on screening at-risk drivers. Through a follow-up medical evaluation, these drivers may seek possible remedies to continue to drive or consider alternative methods of transportation.

However, it is possible that the sudden drop this study observes within the majority of these RAIR figures, following the ages 80 to 89 years cohorts are due to random fluctuations, missing data, or changes in policy or driver behavior. George (2000) explains that nonparametric failure rate functions may describe this “premature wear out and retirement” because no family of distribution functions fits these failure rate functions. Retirement follows the onset of the Wearout Failure Period and causes failure rate functions to decrease.

Unreported collisions may also reduce failure rate functions and occur late in product life, or, in our study, late in driver life. Interestingly, a similar decline is observed immediately after the ages 75 to 79 years cohorts in Western Australia, through driver collision involvement by age, on the basis of rates per 100 million kilometers driven (Ryan and Legge, 1998).

According to the Information Technology Laboratory of the National Institute of Standards and Technology (2004) empirical evidence demonstrates that repairable systems can also be illustrated by bathtub curves when the ordinate is the Repair Rate or the Rate of Occurrence of Failures (ROCOF). However, some but not all devices may illustrate this type of general shape. For example, only 72 percent of United Airlines commercial aviation equipment tends to follow infant mortality rates (Smith, 1992). Different components, like different kinds of human populations, exhibit varying levels of behavior associated with stresses. Hence the three regions may differ according to variables, populations, and time.

Bathtub curves are quite familiar in the literature, especially as these apply to certain product life analyses in reliability engineering. However, these are typically referred to as U-shape distributions in transportation engineering studies and are often associated with one distribution skewed relative to the other. Burg was one of the first to characterize traffic-related collisions in the form of U-shaped (or bathtub-shaped) curves. Burg (1967) and Hills and Burg (1977) showed that the measured visual performance of drivers progressively declined after about age 45 years. It was fairly constant until that age. The U-shaped curve was represented for all types of collisions when the collision rate was plotted on the ordinate and age cohorts were plotted on the abscissa. Young and adult drivers demonstrated significantly higher collision rates. Yet, noticeable increases in collision risk beginning at about age 50 years were evident. Hills and Burg (1977) also identified collision risk, with respect to static or dynamic acuity, in drivers age 54 years and older. In Australia, where drivers age 70 years and older are estimated to comprise 14 percent of Australian fatalities by 2005, a skewed bathtub curve now defines the relative risk of driver fatality per million kilometers traveled. However, the random period appears considerably shorter and the onset of the Wearout Period begins at ages 45 to 49 years. High levels of involvement in a fatal collision are apparent for ages 17 to 20 years and ages 75 to 79 years (Australian Transportation Safety Bureau, 1996).

Similar U-shaped or bathtub curves appear in various traffic violations per 100,000 miles among California driver age cohorts (State of California Department of Motor Vehicles, 1982.) In 1990, U.S. drivers ages 16 to 19 years had the highest collision rate and U.S. drivers age 75 years and older had the highest fatality rate. The fatality rate per 100 million miles, was represented as a U-shape or bathtub curve, where drivers ages 16 to 19 years had the second highest rate of fatalities followed by a decrease. An increase in fatality rate per 100 million miles was evident among the age 55 to 59 years cohorts. Collision rates per million miles were highest for drivers age 16 to 19 years and second highest for drivers age 75 years and older (Massie, et al., 1995). Kim (1996) showed, in the form of a U-shaped distribution, that males ages 15 to 24 years and females age 65 years and older were most likely at-fault in collisions in Hawaii from 1986 to 1993.

Odds of fault were placed on the ordinate, age cohorts on the abscissa. Driver fatality rates, on the bases of age and gender, in 1996, demonstrated that the cohorts age 85 years and older and the cohorts age 16 years constituted the highest fatality rates per 100 million vehicle miles traveled (U.S. DOT, 2000). A bathtub curve illustrated these rates.

In the United Kingdom, however, a different shaped curve emerges: Half of a U where male and female novice drivers are most accountable for collisions. However, the ordinate posts self-reported accident liability, and the abscissa indicates age. (DETR, 2000.) A bathtub curve is observed when accident involvements per year per 1,000 drivers, on the bases of fatal and serious accident liabilities by driver age group (ages 50 years and older) and gender, are illustrated (Maycock, 2002).

To the best of our knowledge and research, there exist no studies that have associated trends in RAIR with bathtub curves. However, in order to identify trends in Figures 30 to 44, it is useful to consider the various regions of the bathtub curves as bases for measurement since our figures, in one form or another, tend to take on the bathtub curve in appearance. More importantly, all of these figures appear to demonstrate the very start of the Wearout Failure Period for both Arizona and Florida begins at approximately age 50 to 59 years. Drivers with visual defects involved in automobile collisions in both states, as shown in Figure 43, seem to have bathtub curve features similar to those of environmental conditions and manner of collisions, especially dawn or dusk lighting conditions as shown in Figure 42. This finding establishes a link between collision involvement and visual defects. This finding also underscores the need for ambient lighting changes and/ or contrast sensitivity testing during vision testing.

Additionally, our RAIR values, especially for the drivers age 80 years and older, are in very good agreement with those computed for Michigan drivers by Stamadiatis and Deacon (1998). Their trends of observed effect of driver age on RAIR also follow a bathtub curve, or U-shaped distribution, as do our RAIR results.

Figure 3. Comparison of Left Turn Manner of Collisions Among Drivers in Arizona and Florida for years 1991 to 2001

According to Figure 3, the Early Failure Period is very short. While both Arizona and Florida drivers feature the onset of the Wearout Period at about the cohorts age 50 to 59 years (RAIR~ 1), a peak occurs among the cohorts age 80 to 89 years (Arizona RAIR ~ 3.9; Florida RAIR~ 4.25) and retires. Drivers age 16 to 19 years are three times less likely to be involved in collisions due to left turns than drivers age 80 to 89 years. Notice how the RAIR values of both Arizona and Florida drivers age 80 to 89 years surpass those of any other age group for left-turn manner of collisions. The results of this study are somewhat in agreement with the findings described by Chandraratna et al. (2002). The general shape of our RAIR for left turn collisions by driver age group appears to be considerably similar except for the component of age 89 years and older cohorts. Although the RAIR values for the ages 16 to 19 years are the same, the RAIR for the age 80 years and older Kentucky cohorts are approximately double the RAIR values of Arizona and Florida drivers. Chandraratna et al. suspect that left turns at intersections may account for these discrepancies among older drivers.

Appendix G includes detailed results and analyses of RAIR values of collision risks associated with environmental factors. Our most interesting RAIR findings are summarized on the following pages.

Figure 4. Comparison of Dawn or Dusk Related Collisions Among Drivers in Arizona and Florida for Years 1991 to 2001

Figure 5. Comparison of Collisions Among Drivers with Visual Defects in Arizona and Florida for Years 1991 to 2001

·       The relative involvement of dawn or dusk-related collisions among both Arizona and Florida drivers are evaluated. Arizona drivers (RAIR~3.6) and Florida (RAIR~ 3.1) drivers age 90 years and older are about twice as likely to be at-fault in a dawn or dusk-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.8; Florida RAIR~ 1.5). The onset of the Wearout Period begins at ages 50 to 59 years for both Arizona and Florida drivers (Figure 42, Appendix G).

·       The relative involvement of corrective lenses-related collisions among both Arizona and Florida drivers are observed. Arizona drivers (RAIR~3.6) and Florida (RAIR~ 3.1) drivers age 90 years and older with visual defects are about twice as likely to be at-fault in a corrective lenses-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.8; Florida RAIR~ 1.5). The onset of the Wearout Period begins at ages 50 to 59 years for both Arizona and Florida drivers (Figure 43, Appendix G).

·       Drivers ages 80 to 89 years in Arizona (RAIR ~ 3.5) are about twice as likely to be at-fault in angle manner of collisions compared to the Arizona drivers age 16 to 19 years (RAIR ~ 1.5). Similarly, the drivers ages 80 to 89 years in Florida (RAIR ~ 3.25) are about twice as likely to be at-fault in angle manner of collisions compared to the Florida drivers age 16 to 19 years (RAIR ~ 1.5), as shown in Figure 30, Appendix G.

·       Drivers ages 80 to 89 years in Arizona (RAIR ~ 1.8) are about 1.5 times as likely to be at-fault in backing manner of collisions compared to the Arizona drivers age 16 to 19 years (RAIR ~ 1.25). Similarly, the drivers ages 80 to 89 years in Florida (RAIR ~ 2.15) are about twice as likely to be at-fault in backing manner of collisions compared to the Florida drivers age 16 to 19 years (RAIR ~ 1.2), as shown in Figure 31, Appendix G.

·       Drivers ages 80 to 89 years in Florida (RAIR ~ 3.25) are about twice as likely to be at-fault in head-on manner of collisions compared to the Florida drivers age 16 to 19 years (RAIR ~ 1.5). However, the drivers 90 years and older in Arizona (RAIR ~ 2.85) are about 1.5 times as likely to be at-fault in head-on manner of collisions compared to the Arizona drivers age 16 to 19 years (RAIR ~ 1.9), as shown in Figure 32, Appendix G.

·       Drivers ages 80 to 89 years in Arizona (RAIR ~ 3.8) and Florida (RAIR ~ 4.15) are about three times as likely to be at-fault in left-turn manner of collisions compared to the drivers age 16 to 19 years in Arizona (RAIR ~ 1.25) and Florida (RAIR ~ 1.45), as shown in Figure 33, Appendix G.

·       Florida drivers ages 16 to 19 years (RAIR~ 2) are more likely to be at-fault in a rear end collision due to higher RAIR values than the cohorts ages 80 to 89 years (RAIR~ 1.9). Contrastingly, Arizona drivers age 80 –89 years (RAIR ~ 2.19) are more likely to be at-fault in a rear end collision due to higher RAIR values than the cohorts ages 16 to 19 years (RAIR~ 1.95), as shown in Figure 34, Appendix G.

  •        Arizona and Florida drivers age 80 –89 years are about twice as likely to be at-fault in a sideswipe manner of collision due to higher RAIR values than the cohorts ages 16 to 19 years (RAIR~ 1.5), as shown in Figure 35, Appendix G.

·       Arizona (RAIR~ 2.45) and Florida (RAIR~ 2.75) drivers age 80 to 89 years are about twice as likely to be at-fault in a clear weather-related collision than the cohorts ages 16 to 19 years, as shown in Figure 36, Appendix G.

·       Florida (RAIR~ 2.75) drivers age 80 to 89 years are about twice as likely to be at-fault in a cloudy weather-related collision than the cohorts ages 16 to 19 years (RAIR~ 1.75). Arizona (RAIR~ 2.95) drivers age 90 years and older are about twice as likely to be at-fault in a cloudy weather-related collision than the cohorts ages 16 to 19 years (RAIR~ 1.75), as shown in Figure 37, Appendix G.

·       Florida (RAIR~ 2.55) and Arizona (RAIR~ 2.35) drivers age 80 –89 years are about twice as likely to be at-fault in a rain-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.8; Florida RAIR~ 1.9), as shown in Figure 38, Appendix G.

·       Florida (RAIR~ 2.6) and Arizona (RAIR~ 2.6) drivers age 80 –89 years are about twice as likely to be at-fault in a fog-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.55; Florida RAIR~ 1.85), as shown in Figure 39, Appendix G.

·       Florida (RAIR~ 2.8) drivers age 80 to 89 years and Arizona (RAIR~ 2.65) drivers 90 years and older are about twice as likely to be at-fault in a daylight-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.75; Florida RAIR~ 1.75), as shown in Figure 40, Appendix G.

·       Florida (RAIR~ 2) drivers and Arizona drivers (RAIR~1.9) age 80 –89 years are about equally as likely to be at-fault in a darkness-related collision as compared to cohorts ages 16 to 19 years (Arizona RAIR~ 1.5; Florida RAIR~ 1.4), as shown in Figure 41, Appendix G.

·       Arizona drivers (RAIR~3.6) and Florida (RAIR~ 3.1) drivers age 90 years and older are about twice as likely to be at-fault in a dawn or dusk-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.8; Florida RAIR~ 1.5), as shown in Figure 42, Appendix G.

·       Arizona drivers (RAIR~3.6) and Florida (RAIR~ 3.1) drivers age 90 years and older with visual defects are about twice as likely to be at-fault in a corrective lenses-related collision than the cohorts ages 16 to 19 years (Arizona RAIR~ 1.8; Florida RAIR~ 1.5), as shown in Figure 43, Appendix G. This seems to demonstrate that these drivers are most likely impacted by dawn and dusk, yet the shape of these skewed bathtub-shape curves also reveals that various lighting, weather, and manners of collision may also significantly affect vision, especially visual defects.

·       Arizona and Florida drivers age 80 –89 years are about twice as likely to be at-fault in a sideswipe manner of collision due to higher RAIR values than the cohorts ages 16 to 19 years (RAIR~ 1.5).

DESCRIPTIVE STATISTICS AND CALCULATED RISKS OF VIOLATIONS/BEHAVIOR-RELATED COLLISIONS IN THE STATE OF ARIZONA, YEARS 1991 TO 2001

The collision rates per 100,000 licensed Arizona drivers on the basis of driver’s license restrictions over an 11-year period, from 1991 to 2001 (Appendix R) are calculated. Drivers ages 25 to 34 years are selected as a baseline since this group surpasses all other age groups with the greatest number of collisions, injuries, and fatalities in both the states of Arizona and Florida (Appendix C and Appendix D). This group is also one of the most populous. The following are determined:

The collision rate of licensed Arizona drivers age 75 years and older, may be as high as twice the rate of drivers ages 25 to 34 years (Figure 82, Appendix B) on the basis of any one of the following:

·       corrective lenses

·       failed to yield right of way

·       made improper turn

These findings support Wick and Vernon (2002). They indicate that higher rates of citations, collisions, and at-fault collisions characterize some groups of visually impaired non-commercial drivers. Collision risks are seemingly greater among drivers with higher levels of impairment and restriction.

·       The collision rate of drivers Arizona drivers age 75 years and older, may be as high as three times the rate of drivers age 25 to 34 years on the basis of any one of the following:

·       automatic transmission

·       left outside mirror

·       full hand controls

·       The collision rate of Arizona drivers age 75 years and older, may be as high as seven times the rate of drivers age 25 to 34 years on the basis of “daylight hours” driver’s license restrictions.

COMPARISON OF AVERAGE INDIVIDUAL RISKS OF COLLISIONS, INJURIES, AND FATALITIES OF ARIZONA AND FLORIDA DRIVERS, YEARS 1991 TO 2001

Risk calculations are often used to quantify radioactive releases and predict nuclear power reactor accident sequence frequencies (McCormick, 1981). Risk methodologies are also useful as a method of ranking risks and prioritizing measures to prevent collisions. In order to manage the underlying causes of traffic-related collisions, injuries, and fatalities, it is necessary for us to identify, estimate, and evaluate the risks associated with these events. Calculations of Average Individual Risk of collisions, injuries, and fatalities of Arizona drivers and Florida drivers allow us to initiate this process. In order to obtain a representative sample of all age cohorts, in accordance with Minimum Uniform Car Crash Criteria (MUCC), ages 16 to 19 years, 20 to 24 years, 25 to 34 years, 35 to 44 years, 45 to 54 years, 55 to 64 years, 65 to 74 years, and 75 years and older, are observed. These results are tabulated in the Appendix Q.

According to the American Institute of Chemical Engineers (2000), we define Average Individual Risk as:

wpe24.gif (10906 bytes)

On the basis of these calculations, our study shows the following:

·       Arizona drivers in all age cohorts have higher Average Individual Risk of collisions than Florida drivers.

·       The greatest Average Individual Risk of collision, Average Individual Risks of Injury, occur among both Arizona (1.14E-01) and Florida drivers (6.71E-02) age 16 to 19 years. This may be due to inexperience, high speeds, and, possibly, alcohol and narcotics.

·       Arizona drivers age 75 years and older are more than four more times as likely to be at Average Individual Risk of collision than Florida drivers of the same age group.

·       The greatest Average Individual Risk of injury occurs among both Arizona and Florida drivers age 16 to 19 years.

·       Arizona drivers age 75 years and older are more than four times as likely to be at an Average Individual Risk of Injury than Florida drivers of the same age group.

·       Arizona drivers age 75 years and older are more than four times as likely to be at an Individual Risk of injury than Florida drivers of the same age group.

·       The Arizona driver age groups with the greatest Average Individual Risk of fatalities include: age 75 years and older cohorts (6.65E-04).

·       The Average Individual Risk of fatalities among Florida drivers is highest among age 16 to 19 years cohorts (2.41E-04). According to Table 2, this quantity warrants public spending to control the hazard.

·       Arizona drivers age 75 years and older are more than 3.3 times as likely to be at an Average Individual Risk of Fatality than Florida drivers of the same age group.

·       According to the Thresholds of Annual Fatality Risk Levels (Table 2, below), the Average Individual Risk of fatalities may encourage people to control these safety hazards.

Table 2. Thresholds of Annual Fatality Risk Levels According to Otway and Erdmann

wpe26.gif (65695 bytes)

H. J. Otway and R. C. Erdmann, 1970, Nuclear Engineering Design, 13, 365, as cited in McCormick,

p.370.

In addition to our global surveys of officials of driver’s license bureaus, statistical studies and risk analyses are generated to determine the possible impacts of vision impairments on collision trends among drivers of various age cohorts in two states with increasing older driver populations. This study seeks to identify cutting edge vision testing equipment that offers improvement over the current vision testing techniques. Comprehensive studies, surveys, and literature reviews are performed. When testing equipment is not identifiable, testing methods previously perceived as “off the beaten track” in driver’s license bureaus are considered: computer automated vision screening and driving simulators.

REVIEWS OF VISION TESTS AND DRIVING SIMULATORS

Introduction

In order to establish criteria for new testing methods it is necessary to evaluate currently available and emerging new tests. Accordingly, evidence of these findings is presented and designs and recommendations of a comprehensive automated driver’s license test system, that includes vision screens and a driving simulator, are provided.

The History and Future of Vision Tests

The current vision standards for driver’s licenses that U.S. states follow are not based on strong empirical evidence through driving performance, vision tests, and safety record. These primarily stem from antiquated visual standards established through Black et al. (1937), a 1925 report approved by the American Medical Association, and widespread implementations and modifications of the Snellen Eye Chart of the 1860s. These standards are typically approved by recommendations from medical, highway, safety, and government agencies. While the Snellen type of test remains solely in use in New York, all other U.S. states, according to our survey, complement this test through the use of vision screening equipment. These allow officials to test both potential and licensed drivers, depending on the state’s rules and regulations, for less than 0.1 percent of the visual field (Fink and Sadun, 2004). Nevertheless, the following is proposed:

·       Ranges of vision loss, as prescribed by the International Council of Ophthalmology (2002), should not only be based on visual acuity.

·       Quantification of visual standards that account for other ocular features, in addition to visual acuity, are direly needed to improve safety and vision, both on and off the roads.

·       New visual standards may also allow for a smooth transition of automation technology in transportation agencies and medical facilities.

As we ride the Information Superhighway, the need for automated vision testing in all driver’s license bureaus prevails. A new system may allow for cost-saving measures associated with testing apparatus, staffing, paperwork, and space. Future vision tests, in addition to those we describe in this chapter, may allow for instant assessments anywhere a driver accesses the Internet, especially with the advent of biometrics and computer network designs to accommodate these features, among many others. Biometrics may allow the measurement of one physical or behavioral characteristic unique to an individual. Physical characteristics include the face geometry, fingerprint, hand geometry, iris, and/or retina. Behavioral characteristics include an individual’s voice and/or signature.

In the United Kingdom, the climate seems very favorable for such possibilities due to implementation of the new national identity card scheme underway there (United Kingdom Home Office, November 2003). The use of web-based or Internet-based automated vision testing at private homes and in other public locations other than a driver’s license bureau office seems likely due to the plans for biometrics within the UK card scheme.

Interestingly, the case in favor of new vision standards and vision testing techniques was adequately addressed on the basis of a large-scale study (n= 30,000) conducted in Canada. Collision risk among Quebec drivers age 70 years appeared to be the same for those with static acuity below U.K. and European standards (6/12 to 6/15 in meters) as opposed to those with better acuity (Gresset and Meyer, 1994).

Vision Screening Tests

A number of vision testers are reviewed, including many of the devices currently in use at driver’s license bureaus in the United States and overseas. These are confirmed through live observations and/ or literature reviews. A number of vision screening and/ or testing devices are highlighted in Table 99 of Appendix S. Interestingly, there is a dearth of empirical evidence demonstrating the effectiveness of each vision testing product in use at all of the United States driver’s license bureaus we contacted. Also, these vision screening machines are severely limited by their static conditions and inability to screen driver’s licensees for both potential eye diseases and vision loss conditions. Although some companies plan to expand their lighting and testing options, these machines completely lack the capability to dynamically simulate driving conditions. Many are not computer automated and therefore burden officials with extra time and paperwork to score and record driver licensee’s test results. Many officials express concerns about cheating and the memorization of material on current driver’s license vision testing techniques. Unlike the written knowledge driving tests, which are primarily automated, none of the vision screening equipment at the driver’s license bureaus is currently available on-line, in or out of the bureau offices. It is, however, possible that these vision screening machines fill voids in clinics, schools, and hospitals for very rudimentary vision screening purposes. However, to the best of our knowledge, there are absolutely no independent and large-scale scientific studies to continue to support their use at ADOT- MVD. The results of our survey of all driver’s license bureaus in the United States, the Commonwealth of Puerto Rico, Australia, Canada, United Kingdom, and New Zealand clearly support these findings. Nevertheless, in an effort to curtail the high number of collisions, fatalities, and injuries in the State of Arizona, a revolutionary approach to improve vision screening tests is essential.

It is important to note that Decina et al. (1990) conducted one of the largest studies on the use of the vision screening machine called the Optec 1000. A pilot vision screening test of 12,710 Pennsylvania licensed drivers was performed at the time of license renewal. Specifically, an Optec 1000, equipped with contrast sensitivity, horizontal visual fields, and static visual acuity tests was used. Decina et al. (1990) suggested that contrast sensitivity impairments appear to indicate the highest collision risk among drivers age 65 years and older. They determined, through an extensive literature search, that there was a weak link between vision screening test failure and driving record. More importantly, they determined that more than 50 percent of the licensees who failed the vision examination were unaware that they were afflicted with vision problems such as cataracts, glaucoma, macular degeneration, and outdated corrective lenses.

Szlyk et al. (1991) sought to improve vision screening methods after identifying limitations in the Keystone and Titmus vision screeners through tests among patients with retinitis pigmentosa and other central field defects. Decina and Staplin (1993) identified a combination of contrast sensitivity, horizontal visual field, and visual acuity tests as an alternative vision screening tool for drivers. These measures appeared to relate directly to collision risk for drivers ages 66 to 75 years and age 76 years and older. They later indicated that they did not associate a relationship between collision involvement and visual acuity or horizontal visual field measures.

In the mid- to late- 1990s, the California Department of Motor Vehicles and the NHTSA took a proactive approach to improving driver’s license testing methods. Several pilot studies were conducted. Hennessy (1996) reported that two of five experimental vision tests, the Pelli-Robson Low-Contrast Acuity Test and Perceptual Reaction Time (PRT) Assessment, the latter that measures visual information processing speed, were considered for a large-scale statewide study in California. In 1998, Janke and Eberhard (1998) conducted a series of driving and non-driving tests through the California Department of Motor Vehicles and NHTSA in an effort to identify older drivers with dementia or other age-related medical conditions. The vision testing component included angular motion sensitivity, dynamic contrast sensitivity, dynamic high-contrast acuity, static contrast sensitivity, static high-contrast acuity, Useful Field of View, etc.

Most recently, Hitchcock et al. (2004) utilized the Optec 1000 and the hand held version to demonstrate that that visual acuity alone may not be sufficient for neurobehavior test paradigms because their subjects, with corrected to normal visual acuity, had varying contrast sensitivity scores. They cautioned about conclusions concerning the Optec 1000 and the hand held version for the use of contrast sensitivity assessments. While both tests provided similar and previous derived contrast sensitivity functions, the contrast sensitivity scores were dissimilar and a slight learning effect appeared to impact most measurements. Differences in spatial frequency scores were attributed to differences in design characteristics affecting viewing.

Our telephone conversation with a representative at Stereo Optical (April 19, 2004) yielded the following information: The Optec 1000 is primarily a driver’s license bureau instrument, with limited capability, designed to measure acuity, with four tests and two slides. The Optec 2000 is more functional and includes 12 tests, 150 different slides, and a depth perception feature. There is an Optec 2000 with peripheral tests. Additional charges apply to an Optec 2000 with remote control capability. Both the Optec 1000 and the Optec 2000 provide day luminescence level. The Optec 6500 provides daytime and nighttime lighting conditions and high and low glare features. No dawn, dusk, or weather conditions are provided in Optec tests.

Also, through an on-line search (Clark, 2001; Scheeres, 2001) and interview with Jeffrey Stewart (2004) of VisionRx, we determined that the State of New Mexico driver’s license bureau conducted a pilot study, for approximately six months in 2001 (Perry, 2004), involving a fully automated visual acuity testing device developed by VisionRx.

However, it appeared as if the focus of the study was ease of possible transition from non-automated to automated vision testing mechanisms as opposed to the scientific collection of data to support further study or implementation of the product. There were no published or independent studies conducted.

Some other vision testing products are also worth mentioning. These include the Useful Field of View (UFOV®), a test developed by Owsley and Ball that allows for a measure of one’s ability to promptly process and react to several targets. The Useful Field of View is a test of visual attention performed and scored on a computer. It measures visual attention skills, processing speed, and sensory function. UFOV primarily quantifies one’s visual selective attention (Owsley, et al., 1998) and complements the cognitive screening process (Myers, et al., 2000). Rizzo et al. (1997) suggest the UFOV among other off-road tests, to assist licensing authorities in the recertification process of impaired drivers. Its effectiveness as a possible neuropsychological evaluation tool may allow it to assess driving risk. Although UFOV may be used to measure driving performance and visual attention skills, in some studies, it has not linked collision status with drivers (Schneider, 2002). Nevertheless, Schneider suggests the possible use of UFOV for a pre-recovery assessment of patients with head injuries to predict their driving ability. He notes that the UFOV may be sensitive to different types and severities of brain dysfunctions. However, Ball et al. (2003) report that the UFOV is strongly connected with at-fault motor vehicle collisions. Also, Rinaldi et al. (2002) indicate that tests such as the UFOV adequately predict driving performance on the low fidelity simulation task. As of January 2005, the UFOV is incorporated in the AAA Roadwise Review™, where it provides a quick and effective measure of visual information processing speed.

A battery of cognitive tests and physical measures for older drivers (ages 55 to 96 years) has been designed and reviewed through the Maryland Department of Motor Vehicles and NHTSA. Although many different vision tests are available, as identified in our comprehensive survey and discovered through our extensive literature review, only one currently meets the specifications of the ESRA DAT™ requirements.

According to the Stereo Optical website, the distance and near testing capabilities of the Optec 6500 may include acuities, color perception, depth perception, low vision E, fusion, lateral and vertical phorias. The Titmus Vision Screeners, for another example, are portable. Manufacturers and distributors claim these products occupy a small space area and are administrable in under five minutes. Most offer a small and limited group of test slides. All offer daylight features. However, they are susceptible to mechanical failure, fatigue, and breakdown. They also are not fully automated.

In January 2005, the American Automobile Association (AAA) released Roadwise Review™, a CD-ROM incorporated the D RIVING  H EALTH ® INVENTORY (D H I) tools (of Trans Analytics LLC) that assess head/ neck flexibility, high contrast visual acuity, leg strength and general mobility, low visual acuity, Useful Field of View, visualization of missing information, visual search, and working memory of drivers. These eight functional areas are considered the most likely predictors of collision risk, as validated by the National Highway Traffic Safety Administration and the National Institute of Aging.

This computer-based screening program is available to non-members and is offered at significant discount to non-members. Many libraries and senior centers will offer free use of the CD-ROM. Roadwise Review™ is not fully automated because an assistant is required to make measurements as the driver takes the test. However, Roadwise Review™ offers one of the best tools available for self-assessment.

The PreView PHP Preferential Hyperacuity Perimeter ™ (PHP), a commercially available product designed for early detection and monitoring of Age-related Macular Degeneration (AMD), is developed by Notal Vision Ltd. and distributed through Carl Zeiss Meditec, Inc. According to the technical specifications of the PHP, it tests the central visual field- 14 degrees- through use of a “dot deviation signal flashed across macular loci” (Carl Zeiss, 2004).

While the PHP may potentially fit into a part of the eye disease component of the ESRA DAT™, we are unable to recommend it at this time on the following grounds: It is not fully automated. A clinician is required for instruction and testing. A stylus is required for a patient to touch a screen where distortion in the lines is perceived to appear. The PHP is chiefly designed as a monitoring instrument for patients who have already been diagnosed with AMD. Driver’s license bureaus do not have a system in place to monitor progression of AMD over time in driver’s licensees or applicants. The PHP is not designed as a screening tool for AMD. The diagnostic procedure also takes about twenty minutes or longer to complete rather than the “rapid test time- five minutes per eye” extensively documented in its marketing literature (Kent, 2003; Carl Zeiss, 2004). This product is, ideally, developed for use by clinicians- not driver’s license personnel. This product has never been proposed for any transportation licensing application (via publication or other materials). No studies have been conducted that associate its usage, for transportation licensing, with reduced collision risk. The record of safety, liability, and performance of the PHP, as these relate to transportation licensing applications, is, therefore, currently unknown. However, for medical settings, the PHP appears to show potential for effective monitoring of wet AMD (Loewenstein et al., 2003; Preferential Hyperacuity Perimeter (PHP) Research Group. 2005. ).

Furthermore, a comprehensive visual field test, the Three-Dimensional Computer Automated Threshold Amsler Test, also called the 3-D Amsler Grid Test (3DAGT), developed by Fink et al. (2003), has great potential to screen and evaluate numerous people for vision impairment over the Internet and in space. As an automated computer-based diagnosis system (Fink, 2002), it may offer patients on earth a very extensive examination when compared to traditional visual field tests. In space, the 3DAGT may provide an autonomous onboard physician to astronauts. Since April 2000, more than 200 patients have been examined with the 3DAGT at the Doheny Eye Institute in the Keck School of Medicine at the University of Southern California (Fink et al., 2003). In 2004, the 3DAGT has accurately evaluated, characterized, and monitored scotomas, regions of reduced or loss of vision within the visual field, in 25 AMD patients and 41 eyes (Nazemi, et al., 2004).

The 3DAGT was based on an Amsler grid-like pattern developed by M. Amsler in 1947 to assess visual function in the central 10 degrees of vision. Wall and Sadun (1986) later improved this perimetric method through the design of threshold level measurement techniques. Fink et al. (2000) generated a three-dimensional computer automated threshold form of Amsler grid testing as we now know it.

The 3DAGT, when modified, may provide quick and easy automated testing of visual field conditions in various kinds of transportation agencies, including a driver’s license bureau setting. A touch-sensitive examination screen (or a regular monitor used in conjunction with a computer mouse) is used to test the visual conditions of patients. Patients cover one eye and, while positioned a fixed distance away from a computer, trace the missing field of vision areas on an Amsler Grid, while focusing on a “varying fixation marker” (Fink et al., 2003, Nazemi, et al., 2004). Different grayscale levels are provided when different degrees of contrast of the Amsler Grid are displayed. These tests offer high angular resolution of 1 degree, rather than the conventional 6 degrees. It may take up to five minutes to test each eye (Fink and Sadun, 2004). Internet-based results are recorded and provided via a three- dimensional illustration and characterization of the scotoma and central hill-of-vision. These are linked to a database for analysis and diagnosis. The 3DAGT successfully detects and screens patients for AMD, anterior ischemic optic neuropathy (AION), central or branch retinal artery occlusions, detached retina, glaucoma, ocular hypertension, and optic neuritis. Several genetic impairments and various types of brain tumors are also identifiable (Tindol, 2000; Fink et al., 2003). These are all conditions that adversely impact driving performance if not readily detected by conventional vision testing equipment.

In the meantime, the depth, extent, location, shape, and slope of any visual field defect can be identified by the 3DAGT in the form of a three-dimensional map. The 3DAGT may eventually allow for the identification of binocular scotomata through binocular visual field data (Fink, 2004). According to our research, the 3DAGT is the only such product to successfully screen for these diseases and to produce independent testing and peer-reviewed publications of its findings.

However, ESRA is aware of crucial modifications of the 3DAGT that are needed prior to deployment at driver’s license bureaus and other transportation agencies.

According to Lawrence Gilbert, Senior Director, Office of Technology Transfer, California Institute of Technology (2004):

“The California Institute of Technology (Caltech) understands that Dr. Wolfgang Fink, Caltech, with your (Sandy Straus) assistance at ESRA Consulting Corporation, intends to modify the “3-D Computer-Automated Threshold Amsler Grid Test”, to present to the Motor Vehicle Division (MVD) of the State of Arizona, for driver’s license vision testing, if selected to proceed with this project. Contingent upon selection on behalf of the Motor Vehicle Division, Caltech intends to enter into a contractual agreement with Dr. Wolfgang Fink, Caltech, including your (Sandy Straus) involvement at ESRA, to create a company to provide products that will enable the development of the technology for this project, and possibly, in other countries and U.S. States.”

Vision Screening Methods in Other Settings

The controversy surrounding the effectiveness and variation of vision screening methods appears to extend beyond the driver’s license bureau agencies and into the U.S. preschools. There appears to be a lack of evidence to support which of the 11 most widely used screening tests adequately detects vision problems in children less than 5 years of age (National Eye Institute, 2004). These studies are of interest because, for example, Stereo Optical, which manufactures the Optec vision screeners, the most commonly used vision testing devices in the U.S. driver’s license bureaus, also supplies preschool vision screening equipment, specifically the Random Dot E Stereoacuity Test and the Stereo Smile Test II. According to our comprehensive national and international survey of driver’s license bureau directors, nearly 79 percent of all U.S. Motor Vehicle Bureaus, 33 percent of all driver’s license bureaus of the Provinces and Territories of Canada, and 12.5 percent of the driver’s license bureaus of Australia, incorporate Optec, in whole or in part, in their vision screening test processes. In the Vision in Preschoolers Study, however, it remains unclear which of the 11 screening tests adequately detects visual acuity impairment independently or in conjunction with other tests (National Eye Institute, 2004).

Following our extensive review of vision testing equipment, we identify the following automated vision test for implementation in the ESRA DVAT™ System (Figure 7):

RECOMMENDED VISION SCREENING EQUIPMENT                                   Table 3. Model and Special Features of Vision Screening Equipment

B1Max™ VACS

·       Fully automated.

·       Rapidly provides high- and low- contrast visual acuity screening in 5 minutes or less.

·       Prevents cheating.

·       Relates measured acuity to collision risk.

·       Presents screening instructions in English and Spanish.

·       Local and Network capabilities

·       Cost-effective

·       Ready for deployment

·       Currently powers AAA Roadwise Review™ in national and widespread use.

·       may be highly recommended based on the performance of the D RIVING  H EALTH ® INVENTORY (D H I) during multiple years of scientific study as a tool used for driver evaluations by the Medical Advisory Board of the Maryland Motor Vehicle Administration.

We also identify our conceptualized version of the 3-D Computer-Automated Threshold Amsler Grid Test (3DAGT), appropriately called the Modified 3DAGT. This version potentially screens any visual disease or injury that affects the central visual field, including glaucoma and AMD of transportation licensees and applicants. Since a prototype of the Modified 3DAGT does not yet exist, we are unable to recommend it for the implementation phase at this time. An automated vision condition test is envisaged as part of the ESRA Dynamic Vision Assessment for Transportation (ESRA DVAT ™).

The 3DAGT test, while outstanding, currently requires significant modification and simplification necessary to employ in a driver’s license bureau setting and/ or any transportation agency where the testing of applicants and licensees are involved. According to Dr. Wolfgang Fink (2004), this could take up to eight months to complete with the assistance of ESRA. Not only does it lack certain features in need of development, but it also necessitates specific modifications and reductions in time to test each driver’s licensee’s or applicant’s eyes.

The 3DAGT also requires complete automation for vision testing at and away from driver’s license bureau sites, simplification for layman usage and scoring, test fraud prevention mechanisms, and linkage to agency databases for record storage and retrieval, especially as these relate to score updates. The Computer-based 3D visual field testing with peripheral fixation points, according to U.S. Patent #6,578,966 (June 17, 2003, by Fink and Sadun) and U.S. Patent #6,769,770 (August 3, 2004, by Fink and Sadun), appears to be developed as a visual field test for patients in the presence of or through visual field test result interpretations by clinicians. The output, as illustrated, in Figures 1, 9, and 11 of these published patent documents, for example, is far too complex for a layman in a transportation licensing agency to interpret or understand.

Yet, automation and networking capabilities, combined with essential modifications and developments of the 3DAGT, should not require the assistance or interpretation of results after the screening process. Therefore, neither clinicians nor driver’s license bureau staff members should be required to oversee and interpret any results. Such staffing would prove neither cost-effective nor beneficial to any transportation agency. However, the 3DAGT is identified based on its successful performance, strong record of publication, and uniqueness. The modified 3DAGT, as envisaged by ESRA, has the potential to significantly transform vision testing for all transportation licensees and applicants.

Modification details of the 3DAGT, devised by ESRA Consulting Corporation, are beyond the scope of this report.

Table 99 of Appendix S includes an overview of many vision screening devices, including the B1Max™ and 3DAGT. It also includes an overview of the vision attention/ cognition test, UFOV®.

DRIVING SIMULATORS: YESTERDAY AND TODAY

From the Past to the Present

The driving simulators of today are products of research tools initiated in the early 20th century. These driving simulators, while largely employed in automotive industry, government, space, military, and academic research fields, in addition to the novice driver and recreational computer markets, among other fields, are also utilized in the medical sector for both research and patient recovery applications. In this chapter, we not only examine the history of driving simulators, but also consider these simulators as a possible testing mechanism in the driver’s license bureaus.

Driving simulators were initially developed to assess the skills and competence of public transit operators in the early 1910s. Over the next four decades, mockup automobiles were equipped with devices to test drivers’ responses to various stimuli. In some cases, mechanical moving scenes or filmed road scenes were shown. By the 1960s, a number of automobile manufacturers, automobile insurance companies, military agencies, universities, and aerospace companies used film approach simulators for studies involving a variety of visual displays (Decina, et al., 1996). However, concerns about automobile safety and collision rates resulted in the development of driving simulator within the United States and overseas. Case et al. were among the first to study performance variables of older and younger drivers in 1970. By 1983, the Federal Highway Administration (FHWA), Human Factors Laboratory, Highway Driving Simulator (HYSIM) was developed as a fixed-base driving simulator, complete with an actual and highly equipped motor vehicle, to conduct a battery of studies ranging from hazard mitigation to human factors. The Swedish National Road and Transport Research Institute (VTI) Driving Simulator, fitted with a sophisticated motion system, and the Daimler-Benz (now DaimlerChrysler) Simulator, soon followed. In the Netherlands, driving simulations were successfully used to assess visual attention and analysis of drivers at about this time (Ponds et al.1988; Brouwer et al., 1991). It was during the 1980s when the surge in popularity of video games and personal computers with improved imagery coincided with advanced interactive driving simulation. These led to complex yet even more realistic driving simulators, complete with imagery, traffic settings, automobile dynamics (e.g., braking or steering reactions), real-time features, and advanced mockup vehicles by the 1990s.

Charman (1997) cites a number of research studies that incorporate driving simulators and the significant correlation between these tools and on-road conditions. He also notes that the use of driving simulators for vision testing of drivers “…remains unproven”. Clearly, no national or international driver’s license bureau we surveyed in Australia, Canada, New Zealand, United Kingdom, and the United States implements driving simulators for driver’s license vision testing purposes. Ideally, these are places where very large numbers of licensees could easily be studied. Nevertheless, a pilot study incorporating this technology, through ADOT, may serve as a prototype for this possible new and emerging vision testing area. These findings allow us to focus our attention on driving simulators and eliminate virtual reality, wearable forms of simulation, and military, truck, and flight simulators from our review. Some software programs seem to merit attention. However, since these do not quite have “the look and feel” of a motor vehicle, these types of simulation were eliminated from further review.

Saluäär, et al. (2000) devised a scheme of classification of simulators as low-level, mid-level, and high-level. Low-level simulators are associated with personal computers, pedals, and steering wheels. Mid-level simulators generally include a mockup automobile and projection screens linked with a personal computer for data collection and study. High-level simulators are more advanced and sophisticated simulators. They usually include or exceed the design of mid-level simulators and may have a Stewart platform or hexapod for support of movement and orientation of the mounted automobile.

The low-level simulators are among the most popular due to widespread use in driver education, medical establishments, rehabilitation settings, and academic projects. Some, low-level simulators, however, are associated with high costs due to size and proprietary features. The mid-level simulators are growing in popularity in government and academic environments due to their seemingly realistic simulations of the “driver experience,” complete with sounds and visual images that are unrivaled in other types of experimental tests. High-level simulators require sophisticated hardware, software, and structural components. Due to the steep costs associated with these types of driving simulators, they are almost all exclusively available at universities, government agencies, and research centers at major automobile manufacturers. The National Advanced Driving Simulator (NADS) at the University of Iowa is an example of a high-level simulator.

Our Internet search yielded 59 different driving simulators from Australia (3 percent), Canada (2 percent), France (8 percent), Germany (14 percent), Japan (3 percent), Korea (2 percent), Netherlands (5 percent), New Zealand (2 percent), Norway (2 percent), South Africa (2 percent), Spain (3 percent), Sweden (3 percent), United Kingdom (7 percent), and United States (42 percent). (See Appendix C.) Only 2 percent of these simulators were not identified with any country or nation. We sought criteria specified in the ESRA DAT ™ and literature review. Approximately 81 percent of the driving simulators reviewed in this study were designed exclusively for research purposes. The remaining 19 percent were comprised of novice driver driving simulators, among other non-research applications.

A number of research driving simulators, particularly those within German and Korean universities and institutes, incorporate the Stewart Platform. This consists of a platform, one triangular face of an octahedron. The base, the opposing triangular face, connects to the platforms by six struts of the octahedron. These struts allow for positioning the platform in six degrees of freedom. Platform orientation and position vary. An actual motor vehicle is typically fitted with measuring devices, linked to a computer for data collection and analyses, and various road images are projected unto large screens within the dome-like structure. Stewart platforms allow for the simulation of low frequency accelerations. While valuable to traffic safety research efforts, the Stewart Platform cannot be placed in a driver’s license bureau. However, such simulators can be used in carefully controlled experimental studies.

Interestingly, vision and motion measurements are typically hallmarks of high-level driving simulators, as opposed to the more mainstream mid-level driving simulators. NADS of the University of Iowa is a high-level simulator due to its numerous advanced features. Many of the driver education driving simulators are geared toward novice drivers whereas the rehabilitation and recovery driving simulators, in use at some hospitals and clinics, are geared toward ill or older drivers. This demonstrates the need for a driving simulator to bridge the gap between age groups and provide low-cost and effective vision and skill assessments. Many driving simulators now actually have “the look and feel” of motor vehicles because they may either be part of actual vehicles or offer a sophisticated combination of aerodynamic structural designs and graphic features.

Driving simulators are now used to assess the visual and physiological effects of fog on driving behavior. Fog reduces visibility and results in numerous motor vehicle collisions. Different densities of fog can be simulated to measure drivers’ visual performance and speed. Studies show that driving speed increases as fog density increases because many drivers mistakenly feel as if they are slowing down (Snowden, Stimpson, and Ruddle, 1998). In addition, these simulators are better equipped to measure real-world driver performance and behavior than they ever were before. For example, some driving simulators offer ambient light and weather conditions. Other simulators, such as those created through Systems Technology Inc., also offer a strong record of peer-reviewed and independent studies of successful poor visibility and testing features of their STISIM driving simulators. The STISIM models, in widespread use in more than national and international academic and industrial settings, including various clients in Arizona, also offer simple self-customization features of different driving scenarios that allow driver’s license bureau personnel the flexibility they require. Moreover, these driving simulators may also serve the dual purpose of screening at-risk drivers and providing an on-the-spot educational tool to the public on how they may exercise caution in order to drive safely on our nation’s roads.

Furthermore, the amount of time for testing is also an issue of concern due to the long queues that are now common in many medical facilities and driver’s license bureaus. Long periods of testing involving driving simulators, particularly those capable of providing comprehensive assessments, may also increase the likelihood of an examinee experiencing a flashback effect or other aftereffect associated with simulator sickness.

According to Johansson and Nordin (2002), a driver’s field of vision require simulations of landscapes, roads, signage, vehicles, etc. on the visual screen of a driving simulator. Visual screens are dependent upon several factors, including acuity, display size, frame rate, resolution, and transport delay. The visual system is imperative to the driving simulator since it supplies visual information to the driver.

Research, Training, and Screening Usage

Driving simulators are usually designed for three purposes: Research, Training, and Screening. Such designs involve criteria that vary according to application.

Nearly every driving simulator in use today originated from research simulators within the military, government, academia, and automotive industries. Driving simulator research devices are generally utilized for empirical, investigative, and experimental usage. The majority of simulators today, as our study shows, appear to be utilized for research purposes.

Driving simulator training devices, however, are used for educational purposes. These are generally targeted toward novices and/ or secondary school students. Such simulators may be used on a daily, weekly, monthly, or yearly basis depending on the curricula developed by instructor(s) and/ or an agency. Driving simulator training models are educational tools used to gauge the performance of the student. Such devices may prove especially useful if our recommendation for accelerating the periods between driver’s license issuance and renewal are accepted by legislation.

In the State of Florida, however, there are currently some proposals through the Florida Senate Transportation Committee (Long, 2005) for the possible use of driving simulators to test the skills of some traffic school students. (Traffic schools typically serve to promote safety, among other purposes, to motorists with traffic violation records.) These driving simulator devices may be used to improve student’s performance through training but should not be deemed as a screening measure unless collision risk and record are safely and adequately documented and associated with such driving simulator usage. This has not been done to date by any entity worldwide. The distinctions between simulators need to be made because training devices cannot substitute for screening devices, or vice versa, unless there has been widespread independent testing and documentation to support such applications and nomenclature. Performance on simulators has not been directly correlated with on-road performance to date.

Furthermore, driving simulator screening devices are primarily used for detecting conditions or impairments that traditional tests cannot. Such devices are based on many years of published studies, results, and trials. For example, driving simulators are now used in research environments to detect or monitor dementia in drivers. Since the incidence of dementia is expected to jump 400% over the next twenty years (Whitmer, 2005), driving simulator screening devices may prove indispensable for transportation license screening purposes.

Driving simulators used for research, training, and screening purposes fill a niche that may otherwise not be available through conventional experimental and testing methods. Further studies must be conducted to enable usage for mass distribution. All driving simulators, irrespective of design, application, and frequency of usage, require safety and liability concerns to be addressed due to driving simulator sickness and other possible aftereffects.

SIMULATOR SICKNESS AND AFTEREFFECTS

What is simulator sickness?

Simulator sickness, or cybersickness, defines possible maladies associated with simulator usage. These include but are not limited to aviation, marine, military, and driving simulators. These feelings of nausea or discomfort occur in some subjects who use driving simulators. Simulator sickness may be triggered through vection, perceived motion, which occurs as a result of a disparity between visual and vestibular perceptual clues (Kennedy et al., 1998). For this reason, vection is sometimes defined as a visually-induced deceptive body motion. While early studies relate primarily to military applications, the widespread use of simulators today allow for further investigations. Kennedy and Fowlkes (1992) characterize simulator sickness as "polysymptomatic", because several symptoms are at play, including blurred vision, cold sweating, concentration difficulty, confusion, drowsiness, eye strain, head fullness, nausea, pallor, and vomiting. Additional symptoms of cybersickness may include ataxia (postural disequilibrium or a lack of coordination), disorientation, dryness of mouth, fullness of stomach, headache, and vertigo (LaViola, Jr., 2000). Since there appear to be several rather than one single source of these symptoms, Kennedy and Fowlkes (1992) define simulator sickness as “polygenic”. Since there are so many factors that cause cybersickness, LaViola, Jr. (2000) reports that “….there is no foolproof method for eliminating the problem.”

Simulator sickness is sometimes classified as a form of motion sickness that may result from abrupt changes in movement or while the body’s orientation is relatively fixed yet exposed to moving visual scenes. Cybersickness differs from motion sickness in that visual stimulation, rather than vestibular stimulation, can trigger cybersickness.

Military studies laid the groundwork for modern simulator development and research activities. Crampton and Young (1953) associated motion sickness with video displays. Havron and Butler (1957) linked flight simulators with motion sickness-like symptoms. Miller and Goodson (1960) reported motion sickness in a helicopter.

There are three controversial theories that govern simulator sickness. These include the cue conflict theory, the poison theory, and the postural instability theory. The cue conflict theory arises from a sensory mismatch between what is expected versus what actually occurs in the simulator. The poison theory evolutionarily relates simulator sickness to the experience of poison or intoxication. The postural instability, unlike the sensory conflicts, defines the decreased ability to stabilize one’s postural motion. The interested reader is encouraged to explore Mollenhauer (2004) for characteristics of these theories, discussions of visual and vestibular systems, and simulator design factors that impact simulator sickness.

Aftereffects

Simulator sicknesses are often characterized by aftereffects. Stanney and Kennedy (1998) document significant and lasting aftereffects, particularly disorientation, elevated nausea levels and oculomotor disturbances following virtual environment exposure. Stanney, et al. (1998) warn of the hazards of disturbed locomotor and postural control following virtual environment exposure. They also cite perceptual-motor disturbances of concern. Recent studies show that three major aftereffects include postural equilibrium, fatigue and drowsiness associated with the Sopite Syndrome, and oculomotor changes such as eyestrain (Kennedy, et al., 1997). Stanney et al. (1998) cite aftereffects that include disturbed vestibulo-ocular reflex (VOR) function, flashbacks, illusory climbing and perceived inversions of the visual field, increased risk of adverse adaptations to subsequent normal environments, postural disturbances, reduced complex psychomotor flexibility, and reduced motor control turning sensations. Kellog, et al. (1980), Kennedy et al. (1987) and Regan and Ramsey (1994) report aftereffects, such as the disorientation of subjects, for several hours after simulator usage. Gower and Fowlkes (1989) document aftereffects that persist for days.

Kolasinski (1996) suggest that the lingering effects of ataxic decrements, operational consequences of simulator sickness, among other delayed aftereffects, triggered through use of virtual reality systems, are of special concern.

Flashback Effects

Flashback effects may result from simulator exposure. These effects may be characterized by flash images or flashbacks that appear, following driving simulator usage. Lackner and DiZion (2003) describe this phenomenon, characteristic of flight simulator exposure, as a consequence of the adaptation process. Head and body movements are associated with “….unusual and inappropriate patterns of sensory feedback.” Several studies underscore the susceptibility of some simulator users to flashback effects, as a type of aftereffect that may not be immediately obvious until hours or days after a simulator session. Kolasinski (1996) refers to this phenomenon as delayed flashbacks.

Baltzley et al. (1989) report that some cases of ataxia and unsteadiness persist for more than 6 hours and, even longer than 12 hours. Flashback effects are a potentially greater risk to driving simulator users because these effects last longer. Baltzley et al. (1997) note the unique incidences of flashback effects and coping mechanisms developed by the pilots themselves that tend to mask the extent of post simulator effects. Hence, flashbacks pose a safety risk through navigation activities (Kennedy et al., 1992).

Past studies document significant health and safety concerns associated virtual environments due to visual flashbacks, disorientation, and disequilibrium that occur up to 12 hours after a simulator session (Kennedy et al., 1995). However, a lack of flashback studies, as these relate to driving simulator usage among all age groups, disallows quantification of such aftereffects. For these reasons, further studies are needed and conservative approaches, what we call “flashback effect management”, are required.

Cyberadaptation Syndrome and Simulator Adaptation Syndrome

The transition between the virtual environment and the real environment is filled with different responses to different simulator users. This transition may be accompanied by varying degrees of simulator sickness. According to Lackner and DiZio (2003), virtual environments and the aftereffects that occur on the return to the normal environment are characterized by “full set of behavioral, psychological and physiological changes.” Cyberadaptation Syndrome, or Simulator Adaptation Syndrome, may describe this journey and its characteristics.

Stanney and Salvendy (1998) report that Simulator Adaptation Syndrome (SAS) underscores the need for standard measurement approaches and sensorimotor discordance identification that trigger this reaction to driving simulators. Simulator Adaptation Syndrome (SAS) creates autonomic symptoms, such as nausea, in some drivers of driving simulators. According to Rizzo et al. (2003), these may be due to a broad range of simulator displays, devices, technologies, and scenarios- all that may present a drawback to testing if not properly monitored and reviewed.

Factors of Simulator Sickness

Kolasinski (1996) cite several factors associated with simulator sickness, including age, degree of control, duration of task, field of view, gender, and lag. Kennedy et al. (1997) identify the following five classes of determiners of simulator sickness as equipment and technical system factors; user characteristics, duration of time in the simulator; simulator usage schedule and kinematics. LaViola, Jr. (2000) cites display and technology issues, position tracking error, lag, and flicker as several contributing factors to cybersickness in virtual environments. Some individual factors, as discussed, include age, gender, illness, and position in the simulator. The time between the subject beginning an action and the action occurring in the virtual environment defines lag. According to Pausch et al. (1992) delays in lag can result in cybersickness. Nevertheless, proper control of imagery, movement, field of view, and timing, among other factors, of driving simulator sessions may reduce the likelihood of simulator sickness.

Simulator Sickness Studies

Baltzley et al. (1989) report that from 6 to 62 percent of military pilots experience simulator sickness. Regan and Price (1994) and Cobb et al. (1998) identify simulator sickness symptoms of eyestrain, headache, nausea, and malaise after 10 –20 minutes of virtual reality exposure in non-pilots. Kennedy et al. (1995) reveal that 30percent to 50 percent of 2,000 flight simulator testees experienced simulator sickness, such as Sopite Syndromr, characterized by fatigue or drowsiness, following a simulator session. They conclude that there exist major safety implications, particularly for elderly persons, who may be exposed to driving simulators. Although rates are dependent on the type of simulator, Gillingham and Previc (1996) document simulator sickness in 40 percent to 70 percent of pilot trainees following use of high-quality military flight simulators. Kennedy et al. (1997) cite reports of simulator discomfort from United State Navy pilots and the United States Air Force where simulator sickness could be detected in almost all simulators. Baltzley et al. (1997) note that simulator studies of United States Coast Guards in training over several weeks led to the conclusion that unsteadiness and postural disequilibrium are the post effects that prompt the greatest safety concerns. Stanney et al. (1998) cite several studies where 80 percent to 95 percent of participants in a number of virtual environment studies reported adverse symptoms, and 5 percent to 30 percent experienced symptoms severe enough to end participation. Kennedy et al. (2001) estimate, on the basis of a large sample study, that 10 to 20 percent or more testees will exit a simulator session after a few minutes due to simulator sickness.

The Simulator Sickness Questionnaire

In 1965, Kennedy and Graybiel (1965) developed a motion sickness questionnaire that, following several modifications, formed the foundation for today’s simulator sickness questionnaires.

The Simulator Sickness Questionnaire (SSQ) quantifies simulator sickness and divides the symptoms according to disorientation, nausea, and oculomotor discomfort (Kennedy, et al., 1993). It allows for the monitoring of simulator performance with data from a computerized SSQ. The questionnaire provides a more valid index of overall simulator sickness that distinguishes it from motion sickness. The SSQ more accurately identifies the basis of simulator sickness.

Stanney et al. (1998) report that, while this questionnaire was originally designed as an assessment tool for aircraft simulator system subjects, it allows subjective symptomatology assessments and scores on simulator sickness subscales. SSQ scoring is based on factor analytic models (Kennedy et al., 1992).

Field of View and Flicker

Conflicting findings suggest that wide field of view may not greatly impact the susceptibility of cybersickness. Although Lestienne et al. (1977) report intense sensations of motion sickness with a wide field of view, Anderson and Braunstein (1985) document similar findings with a reduced field of view. Although the intensity of simulator sickness may be independent of screen size or number of screens of a driving simulator, Hettinger and Riccio (1992) associate vection with wide field of view displays.

Allen et al. (2003) conducted a pilot study of novice drivers using different driving simulator system configurations, including a single monitor desktop, three-monitor “wide field of view” desktop, and a cab with a wide field of view projection. Their objective was to show that a personal computer-based driving simulator system could be used in both research and non-research settings. Approximately 91.7 percent of the participants did not report any discomfort. Single monitor displays demonstrated the highest number of surpassable speed limits. The lowest number of surpassable speed limits, on average, were shown by Wide Field of View Desk Top, composed of three computer monitors. Approximately 2.8 percent indicated that the simulator systems made they feel queasy. These symptoms did not appear to be influenced by increasing display field of view.

Jeng-Weei et al. (2002) reports that the rate of nausea decreases when many clouds are used as an independent visual background. This may be due to the naturalness and stableness associated with clouds.

Edwards et al. (2003) associate large field of view, e.g., 150 degrees, with simulator sickness. Therefore, field of view, speed settings, and time duration of the driving simulator test may limit simulator sickness. Johansson and Nordin (2002) demonstrate that a lack of synchronization between the visual and motion systems also contributes to simulator sickness (Johansson and Nordin, 2002).

Sparto et al. (2004) report that wide field of view devices result in greater simulator sickness. They urge safety testing prior to any use in a clinical setting. However, they show that 69 percent of subjects did not experience simulator sickness symptoms when a wide field of view environment was used to gauge self-reported tolerance to movements. They theorize that reduced exposure time, display device type, content and nature of task, and significant rest breaks between trials may all influence susceptibility to simulator sickness.

Kennedy et al. (1988) link vection with increasing retinal periphery stimulation. McCauley and Sharkey (1992) relate driving simulation motion and stimuli to vection. LaViola, Jr. (2000) notes that the complexities of the visual system account for many more vection-related physiological factors. These may be evident during driving simulation when the optical flow patterns of traffic, structures, and roads travel past the examinee’s periphery. Wider field of views may also increase the susceptibility to flicker, which can cause eyestrain and other cybersickness symptoms.

There appears to a tradeoff associated with 1-screen and 3-screen simulators. While the 3-screen models may provide more realistic views, they may also consume more space and induce more cases of simulator sickness among subjects.

In order to reduce simulator sickness and improve task performance, there are effective image resolution requirements in aviation training simulators at the Federal Aviation Administration (Mollenhauer, 2004). It is unclear now, based on our literature review, whether there are such requirements exist in any government agencies as these relate to driving simulators due the various applications.

Gender

In several studies, females are more likely than males to report higher simulator sickness ratings (Reason and Brand, 1975; Kennedy et al., 1995; Rinalducci et al., 2002; Allen et al., 2003; Edwards et al., 2003; Rizzo et al., 2003). This finding may also relate to the size of the field of view, which may be larger among females.

Incidence of simulator sickness

The incidence of simulator sickness varies from application to application. In driving performance studies, Rinalducci et al. (2002) shortened driving simulator tests to prevent simulator sickness. However, approximately ten percent of participants from three different age groups reported simulator sickness and were unable to continue testing. Lee et al. (2003) determined that approximately 9 percent of the participants in their study experienced “simulator sickness,” although a very short and mild degree of dizziness after completing the driving simulator session. Yet, this did not affect their performance. According to Edwards et al. (2003), simulator sickness prevented forty percent of recruited older participants from completing their study. They indicated that some participants complained about disorientation, dizziness, and nausea, while others were observed in bouts of sweat and paleness that led to increased head movement, repeated swallowing, and vomiting.

Impacts of Cybersickness

There appears to be a lack of research on cybersickness and the impacts of freedom of movement or control necessary to “….minimize the adverse effects of human-virtual environment interaction” (Stanney et al., 1998). Little or no control over simulator movements may account for the susceptibility of crewmembers and pilots to sickness (Reason and Diaz, 1971; Casali and Wierwille, 1986). Although user-initiated control may impact symptoms of simulator sickness (Stanney and Hash, 1998), Rizzo et al. (2003) investigate whether driver SAS initiate poor control of a simulator vehicle or if vehicle control is weakened by SAS.

Studies of At-Risk Drivers

Rizzo et al. (2003) evaluated the effects of SAS on driver performance of at-risk older drivers, including patients who were diagnosed with Alzheimer’s disease and stroke. Feelings of discomfort accounted for an early simulator drop out rate of 21 percent of the 164 drivers. Body temperature increase, dizziness, light-headedness, nausea, and nervousness were correlated with high levels of discomfort scores through questionnaires provided to drivers immediately after driving simulator usage. These findings were in good agreement with earlier studies by Kennedy et al. (2001). Furthermore, Kolasinski (1996) suggests identification, training, and warnings as methods to reduce simulator sickness in at-risk users.

Simulator Sickness Mitigation Strategies

Mitigation strategies vary among simulator users. Some try conventional approaches while others incorporate various devices.

LaViola Jr. (2000) suggests sitting, rather than standing, in a virtual environment may decrease cybersickness symptoms because it would diminish postural control. He further describes ways to reduce cybersickness, including the use of motion platforms, direct vestibular stimulation, rest frame usage, and an adaptation program. However, there appears to be a tradeoff with the adaptation program, which, while helpful in the virtual environment, seem to increase the likelihood of aftereffects and flashbacks due to an increase in exposure time, among other factors.

Mollenhauer and Romano (2002) incorporate the application of the ReliefBand®, as a simulator sickness mitigation device. Patients who experience nausea from pregnancy, chemotherapy, and motion sickness sometimes use the ReliefBand to impart a mild electrical stimulation to combat nausea. According to the ReliefBand website (2005), the ReliefBand Device should always be used under medical supervision. There are also risks to pacemaker users who may experience interference through use of the device.

Clearly, use of ReliefBand, and/ or any device that imparts electrical simulations, introduces a whole new set of possible liability issues, especially for transportation licensing agencies, among others, due to the possible side effects to different people.

Future Simulator Sickness Studies

While military studies have contributed to simulator sickness studies for more than five decades, the popularity of driving simulators today, in educational, research, and public distribution, merits further review and studies. According to Kolasinski(1996), “….longer-lasting effects, especially those such as flashbacks and ataxia, pose a safety risk to both users of simulators and to others… It is important that ataxia, as well as sickness, be investigated because…. of the many possible liability issues surrounding widespread use of such systems.” She states that such sicknesses threaten the use and application of driving simulator products due to liability concerns.

A lot of the available literature relates directly to the novice, particularly, aviation trainees. These studies generally, fail to target older simulator users and those at-risk. Such users may have special needs and reactions that need to be addressed. There is, therefore, a need for further studies on the flashback effect, especially as these relate to older and at-risk drivers, among others. Kennedy et al. (1995) suggest that for future research, simulator exposure time should be carefully recorded in order to assess its impact on aftereffects. Stanney et al. (1998) also recommend studies of “….delayed effects from virtual experiences…. in order to ensure the safety of users once interaction with a virtual world concludes.”

According to Kennedy et al. (1997), “Formal information exchange programs should be instituted to not only aid industry in reducing product liability punitive awards, but it is in the best interest of the public.”

At the Seventh International Conference on Human Computer Interaction in 1998, a special committee underscored the importance of measurement approaches, standardization, and identification of sensorimotor discordances of aftereffects. Many national and international organizations continue to meet to review and discuss simulator safety mechanisms, among other driving simulator issues.

SAFETY RECOMMENDATIONS

While driving simulators appear to offer a cost-effective alternative to screening all drivers, there are liability issues that every agency needs to consider prior to implementation, application, or use of driving simulators for transportation license testing purposes.

Kennedy (1995) proposes certification tests to avoid the accidents that can result from simulator aftereffects, especially when driving, flying, or roof repair. He warns “… simulator operators, developers, and manufacturers could be liable” since “an individual may be injured as a result of simulator exposure”. According to Kennedy et al. (1997), there now exists, from virtual environments to real-world settings, “the transfer of maladaptive cognitive and/or psychomotor performance…. with, as yet, unknown adverse legal, economic, individual, and social consequences.” Kolasinski and Gilson (1998) conclude that simulator sicknesses and aftereffects “….pose severe safety risks and raise serious liability issues.” Surveys of ten simulators at six different Naval and Marine Corps site yield that simulator sickness, especially within flight simulators, occurs “…during maneuvers that do not occasion them….” Hence, Kennedy et al. (1989) recommend monitored and restricted activities, such as driving, immediately after simulator sessions due to safety concerns.

Similarly, Stanney et al. (1998) recommend that following simulator sessions, “….bans on driving, roof repair, or other machinery use…. may be necessary.” They warn that the subjects who feel less affected or ill when they exit such simulator sessions may, in fact, be at greatest risk of simulator sickness and/ or its aftereffects, as documented by Kennedy et al. (1995). Such concerns led to grounding policies at the Navy and Marine Corps after simulator flights (Kennedy et al., 1989, LaViola, Jr., 2000).

Stanney et al. (1998) further note “Of equal importance is ensuring the health and welfare of users who interact with these environments….If the human element in these systems is ignored or minimized, it could result in discomfort, harm, or even injury. It is essential that VE developers ensure that advances in VE technology do not come at the expense of human wellbeing.” They also warn of the negative social implications and impacts resulting from the user’s misuse of the virtual environment (VE) technology.

It is very likely that a little simulator sickness discomfort may be a small price to pay to weed out at-risk drivers. These drivers pose a risk to themselves as well as to other motorists. However, driver safety and health cannot be compromised at the expense of driving simulator usage. As long as driving simulators are integrated in the driver’s license testing process, as we propose, then the comfort and safety of all subjects must be ensured.

Although driving simulator usage poses a safety concern, we suggest that transportation agencies and medical facilities have examinees sign waivers, indemnification, and release of liability waivers and not drive, fly, and/ or perform roof repair, and/ or operate any machinery until at least 72 hours have elapsed following a simulator test session to reduce the possibility of potential liability for any possible aftereffects, flashbacks, and/ or simulator sicknesses that some subjects may experience. We also urge these agencies to implement driving simulators with long histories of success, implementation, safety testing, and usage as these relate to both novice and older drivers. These should be documented through numerous independent and peer-reviewed publications over the last ten years in several different subject areas. Although many factors may account for simulator sickness and its aftereffects, age appears to be among these aspects. As age increases, susceptibility of motion sickness rapidly rises (Gahlinger, 1999). Hence older drivers may be more susceptible to simulator sicknesses and discomfort. Older drivers may have special needs that not all driving simulators provide. Transportation may need to be arranged for driving simulator testees. A panel of independent scientists and physicians should work closely with these agencies to monitor such progress and performance.

We strongly recommend that transportation agencies and medical facilities have examinees sign waivers, indemnification, and release of liability waivers and not drive, fly, and/ or perform roof repair, and/ or operate any machinery following all other automated forms of testing. Since these may not incorporate simulation, and the effects, if any, may be very short, a team of independent physicians and scientists should determine the appropriate amount of time to refrain from such activities.

Ideally, a pilot test phase should be implemented to determine the feasibility of driving simulator usage for any transportation license testing purposes.

RECENT AND CURRENT DRIVING SIMULATOR RESEARCH

Increases in both driving simulator and on-road driving collisions have been linked to peripheral vision weaknesses (Keltner and Johnson, 1992; Szlyk et al., 1992; Szlyk et al., 1993). Several studies document use and application of driving simulators as a viable option for driver safety analyses. Some studies focus exclusively on dementia drivers. Lundberg (2003) divides these dementia driving studies into two categories: those that relate to collision involvement or driving difficulty and those that are geared toward driving performance predictability.

Szlyk et al. (1993) used driving simulators to assess driver safety in visually impaired and non-impaired drivers with juvenile macular dystrophies. Szlyk et al. (1995) used an interactive driving simulator to measure compromised vision and visual field loss of drivers of all ages and visual conditions. They successfully identified weaker driving skills, increased eye movements, and slower simulator driving speeds in drivers age 50 to 83 years than the drivers age 19 to 49 years, through an 8-minute driving simulator session. They also associated collision risk with compromised vision and visual field loss. Several subjects were diagnosed with AMD, hemianopsia (when one or both eyes are characterized by blindness in one half of the visual field), among other disorders and diseases.

Decina et al. (1996) conducted a useful study of existing simulators for improving the safety training of novice drivers, primarily younger drivers. They determined that high costs and limited accessibility of driving simulators were a deterrent for novice training applications. Although they found that the majority of driving simulators were employed for research and training purposes, Decina et al. (1996) suggested a type of network setup “…enabling simulators in remote locations to share scenarios, instructions, and scoring…”

Rizzo et al. (1997) utilized the Iowa driving simulator to observe strong predictors of collision in drivers with Alzheimer’s disease (AD) and drivers without dementia. Visual and cognitive test scores were used to determine collision susceptibility in drivers with mild dementia. No visual acuity differences, apart from a slight reduction in static spatial contrast sensitivity were observed in the drivers with AD. Yet, several poor neuropsychological measures were apparent in the mild to moderate dementia group of AD drivers. Approximately 29 percent of the AD drivers engaged in the driving simulator study experienced collisions. These findings, among others, led Rizzo et al. to support the idea that some AD drivers with mild dementia “….remain fit drivers and should be allowed to continue to drive.” According to Rizzo et al. (1997), simulated collision avoidance scenarios “….provide demonstrations of driver behavior that cannot be obtained any other way. The simulator record can be compared to that of the black box flight recorder from a downed aircraft, yet no one is injured.” Owsley et al. (1998) associated collision risk and poor performance in a driving simulator with significant binocular visual field loss.

The University of Michigan Transportation Research Institute driving simulator consists of a mockup of a car based on network of Macintosh computers and, among other things, a 33 degree horizontal and 23 degree vertical field of view. In an effort to assess the visual demand of drivers in three age groups (18 to 24 years, 35 to 54 years, and 58 to 68 years), Tsimhoni and Green (1999) illustrate that the radius of curvature creates a higher visual demand, the proportion of time a road is visible, among the driver cohorts ages 58 to 68 years.

Westlake (2000) supports the use of driving simulator assessments and advanced vision tests, among other approaches to effectively predict collision involvement through these types of cognitive and perceptual tests. Szlyk et al. (2002) promotes the use of driving simulators as screening tools for dementia drivers. Szlyk et al. indicates that driving simulators also allow the potential to identify neuropsychological tests that provide driving performance predictability. Ball (2003) cites driving simulator performance studies that are associated with useful field of view. Lee et al. (2003) encourage the use of driving simulations as an initial screening tool for at-risk drivers through their successful study to assess the driving performance of drivers ages 60 to 88 years. They show that the simulated driving assessment results were in good agreement with the on-road assessment results. These assessments identify decrements associated with cognition, and medical, peripheral vision, and sensory conditions. Hence such tests may also be used to study the driving performance of patients with AD. Ball and Owsley (2003) and Duchek et al. (2003) support evaluation and more frequent reevaluation of drivers with mild and very mild stages of dementia of the Alzheimer type.

In the Netherlands, driving simulators, specifically, the mockup of a car positioned before a 165-degree by 45-degree projection screen, continue to proved effectiveness in evaluation of the impacts of visual field defects on the driving performance of driver cohorts ages 37 to 86 years (Coeckelbergh et al., 2002). An experienced driving examiner from the Dutch Driver's License Authority (Centraal Bureau Rijvaardigheidsbewijzen, or CBR) verifies these results through a standard road test for drivers who do not satisfy the vision requirements for driving.

At the University of Iowa Hospitals and Clinics, the Simulator for Interdisciplinary Research in Ergonomics and Neuroscience (SIREN) was set up to assess at-risk drivers through a mockup of a car equipped with a 150-degree forward view and a 50-degree rear view. Studies targeted patients with AD, drowsiness, old age, Parkinson’s disease, sleep apnea, or traumatic brain injury (Rizzo, 2002). SIREN varied elevation, roadway type, roadway surface conditions, signal control, and visual environment to optimally test driver performance.

Currently, two major studies, among many worldwide involving driving simulators, are underway at the University of Iowa and Harvard University. At NADS at the University of Iowa, researchers seek to validate a vision test for simulated driving performance tests (Galluzzo, 2004). However, this study is limited to contrast sensitivity testing. At the Schepens Eye Research Institute at Harvard Medical School, research is now in progress to study driving in visually impaired patients using driving simulators. Dr. Eli Peli and his team of researchers are building specific scenarios using a simulator from FAAC Incorporated of Ann Arbor, Michigan. After more than 3.5 years of various phases of development, data collection is planned for July 2004. According to Dr. Peli, the FAAC simulator “…appears to provide abilities to create scenarios and really analyze data” (Peli, 2004). Although the basic driving simulator tool is in use for driver training programs at several different government agencies (FAAC Incorporated, 2004), at this stage, it does not seem to be marketable for or applicable to driver’s license vision testing. Meanwhile, some clinics in Florida already use DriveAble®, a driving simulation used to measure on-road driving skills, and medical and cognitive weaknesses (Florida At-Risk Driving Council, 2004; Jenks, 2004).

Presently, a study is in progress at the National Advanced Driving Simulator (NADS) at the University of Iowa in an effort to validate a vision test for simulated driving performance tests (Galluzzo, 2004). However, this study is limited to contrast sensitivity testing. At the University of Queensland in Australia, touch screens are being developed to detect older motorists who are suffering from the early signs of Alzheimer's. These two-hour tests, including road simulation, are planned for full-scale implementation in General Practitioner surgeries and health centers within three years (Atkinson, 2004).

Drive Safety, Inc. of Utah develops a number of driving simulators for national and international usage, especially in the research and development areas. They also perform safety tests of other driving simulator products. While Drive Safety, Inc. publishes their list of driving simulator users in the private and public sector, they do not disclose the names of the companies whose driving simulator products they test. According to private communication with Drive Safety, Inc. (2004), there are substantial fidelity concerns that their team of scientists and psychologists identify.

Furthermore, Hopkin et al. (2004) support driving simulators, among other assessment techniques, in order to research and implement adequate screening mechanisms for dementia drivers and other at-risk drivers in Ontario, Canada, and elsewhere. They cite studies that show dementia drivers are two to five times more susceptible to collision involvement.

Ideally, the driving simulator could be used to supplement current vision testing assessments of at-risk or high-risk drivers to screen those who require further medical evaluations. Since driving simulators have contributed to safety improvements on our roads and in our automobiles, they can and should be considered for use in driver’s license testing practices. Also, Roenker et al. (2003) discuss administration and scoring anomalies in road tests that are less prevalent in driving simulators due to computerization.

Following a thorough review of many interesting driving simulator products, as tabulated in Table 100 of Appendix T, we identified the best simulators on the basis of results of a questionnaire ESRA developed. Although respondents requested confidentiality of their questionnaire responses, these questions included but were not limited to the following on their driving simulator product(s):

·       Complete references and contact information

·       Safety testing such as flashback effect studies

·       Identification of any special features or unique functions

·       Complete bibliographic information of any published or peer-reviewed
studies on any driving simulator products.

·       Amount of time required to complete tests.

·       Instant scoring mechanisms.

·       Network capabilities.

·       Bilingual capabilities.

·       Full automation.

·       Cost of each unit, customization, warranties, training, shipping, etc.

·       Discounts.

·       Availability and Applicability.

Following a questionnaire developed by ESRA, and, as tabulated in Table 100 of Appendix T, an extensive review of national and international driving simulators, we identify the following three simulators for implementation in the ESRA DVAT™ System (Figure 7):

RECOMMENDED DRIVING SIMULATORS 

Table 4: Models and Special Features of Driving Simulators

Model and Special Features

Systems Technology, Inc. STISIM Drive ™ Model E-01 Driving Simulator (1-screen with cab) STISIM Drive ™ Model E-02 Driving Simulator (1-screen desktop) STISIM Drive ™ Model E-03 Driving Simulator (3-screen with cab) STISIM Drive ™ Model E-04 Driving Simulator (3-screen desktop)

·       numerous self-customization driving scenarios.

·       1 or 3 screen display models.

·       driver behavior tests.

·       Networking capabilities.

·       PC Windows capabilities.

·       ideal for vision status tests as part of the ESRA DAVT™ and ESRA VAPT™.

·       ambient and simulated light and weather conditions.

·       simulation similar to visibility and contrast reduction due to fog, rain, and snow.

·       based on very strong record of publication (more than 50 peer-review studies).

·       Recent peer-reviewed and published studies on older drivers include : Bolstad, 2000; Bolstad, 2001; Freund, et al.,2002; Hassanein et al.,2003,; Lee, 2002; Lee et al., 2003.

·       international applications.

·       associated with STISIM users and applications at more than 66 national and international universities and medical institutions, 33 companies, and 13 U.S., foreign, and state agencies.

·       clients include Arizona Department of Public Safety and the Tucson Police Department.

While we initially considered Raydon Corporation Virtual Driver™ driving simulator products to appear very promising, we were unable to recommend any of their products at this time due to the following reasons: In February 2005, information on pricing, economies, warranties, safety and performance records, published studies, and references, among other liability concerns was unavailable. There was also no indication that any of the Raydon Corporation products were independently and extensively tested on older drivers and/ or at-risk drivers. Raydon Corporation declined to provide any documenttation of this information. We therefore have concerns about the safety and performance record of the Raydon Corporation driving simulator (Virtual Driver™) products at this time.

Raydon Corporation also would not disclose the networking capabilities of its products and therefore it is unclear as to whether or not their products have automation and networking capabilities. Such features are essential to automated testing and, as demonstrated in this report, the cost-effectiveness of new driver’s license testing systems and applications.

Through nearly one century of usage, driving simulators, in the automotive industry, government, law enforcement, space, military, medical, academic research fields, and driver education programs contribute to quality improvements of safety on our roads, in our military operations, and through our patient recovery processes. On the bases of these applications, as well as recent studies we highlight, the addition of a driving simulator, as a possible screening device of a comprehensive vision testing system, merits further consideration. Driving simulators appear to optimize the ability to test driver response to common road, lighting, weather, and pavement hazards without the risk of collision, fatality, or injury of driver, passenger, or driver’s license bureau personnel. Ideally, a three-screen driving simulator could be used to supplement current vision testing assessments of at-risk or high-risk drivers to optimally screen the vision of those who require further medical evaluations, in particular, dementia drivers and others with neurological disorders. Since driving simulators have contributed to safety improvements on our roads and in our automobiles, they can and should be considered for use in driver’s license testing practices once the safety and liability issues are adequately addressed. At a time when gas prices are on the increase, and driver’s license bureau staffing and motor vehicle maintenance costs prevail, driving simulators may prove as cost-effective and “environmentally friendly” supplements to traditional driver’s license vision tests once all associated safety concerns are addressed. The ESRA DVAT™, though two automated tests (to test vision condition and function) and one driving simulator (to assess eye status and strategy) constitute a system that covers the most comprehensive measures of visual acuity, condition, function, performance, and status measurements that we know of for any transportation licensing agency, including the driver’s license bureau setting.

CONCLUSION

People are living longer and many older adults are licensed drivers now more than ever before. Based on these trends, a surge in the number of licensed older drivers over the next 10 years can be expected. These changes may also include a significant rise in the number of collisions, injuries, and fatalities among older drivers unless action is taken now to weed out at-risk drivers. As our population significantly increases over the next 50 years, the demand for more effective driver’s license screening tools intensifies. These issues need to be addressed in each state and country now as the older driver population grows and necessitates adequate accommodations to improve safe driving. The new systems and procedures ESRA now presents may also reduce the incidence of fraudulent schemes and issuances of driver’s licenses, commercial driver’s licenses, and hazardous materials transportation licenses.

The core of the problem of adequately identifying visually impaired drivers not only relates to the vision testing methods, but also to the fundamental definition of vision loss, which, according to the International Council of Ophthalmology (2002), is based on visual acuity.

Quantification of visual standards that account for other ocular features, in addition to visual acuity, are direly needed to improve safety and vision, both on and off the roads. Snellen acuity measurements, the most widespread within the United States and in other countries, account for less than 0.1 percent of the visual field (Fink and Sadun, 2004). The visual standards for operating motor vehicles in the United States largely stem from 1925 (Black et. al, 1937). Increases in the number of U.S. roads, improvements in road and motor vehicle designs, and dramatic shifts in population changes are apparent from 1925. However, according to Arizona Administrative Code, Title 17, section R17-4503, 2002, Vision standards, visual screening equipment or the Snellen Chart is used at the ADOT Motor Vehicle Division for testing purposes. New visual standards that incorporate the current visual acuity measures, will facilitate the process and procedure of comprehensively identifying all transportation licensees through application of the ESRA DVAT™.

For the sake of driver safety, an increasing number of states modify driver’s license policy, renewal procedures, and vision testing frequencies. Florida, most recently, follows a newly enacted law for all drivers age 80 years and older to either complete an on-site vision screening test at a local driver’s license bureau or obtain certified vision testing results from a physician. A similar law follows enactment in Virginia. In Oregon, vision screening is tested on-site for every licensed driver age 50 years and older at the time of license renewal every eight years. While these on-site driver’s license bureau examinations may, in the short term, allow for limited identification of drivers with visual impairments, they completely fail, in the long term, to improve the actual vision testing process and screen the most at-risk drivers. The methodology remains unchanged so a placebo effect is effectively created. However, the State of Arizona is the first to commission such a unique study and to allow ESRA to present its designs of a new fully automated system (ESRA DAT™) for driver’s licensees and applicants.

This includes a new vision testing system, the ESRA DVAT™. In the event our recommendations are accepted, our ESRA DVAT™, a comprehensive and automated vision testing system (Figure 7) will be the first of its kind in a driver’s license bureau in Arizona and, possibly, the world, to implement the most sophisticated technology available to screen drivers for vision condition, function, and disease. The ESRA DAT™, including the ESRA DVAT™, may also benefit other transportation agencies, including but not limited to licensees within aviation, rail, and maritime areas.

Despite abundant research in other areas, little is known about the relationships between driver’s license visual testing methods and collision risks. The current testing methods appear to be inadequate. No empirical evidence is available to support the effectiveness of these products. A lack of automation and comprehensive screening measures may account for this dearth of data. Nevertheless, it is likely that little or no relationship has been established between visual acuity and collision risk. We, therefore, support the Florida At-Risk Driver Council’s (2004) recommendation, “Like visual acuity, other vision deficits must be managed more frequently and corrected whenever possible to provide a safer driving environment.” Hence it is equally important for us to demonstrate the safe and effective use of the products we identify in whole and/ or in part of the ESRA DVAT System ™ and ESRA DAT™ System. Networking capabilities are essential for expansion and integration of other features, such as cognition, driving skills, and written tests, among other elements, associated with transportation licensing procedures. Bilingual testing features, particularly in the United States, are also crucial for licensees whose primary language may not be English. Driving simulators, such as the STISIM models, that have been successfully tested and peer-reviewed, over long periods of time, through published studies, especially on both novice and older drivers, are particularly useful because of the needs of older drivers that not all driving simulators address.

While our objective is to identify the best product available to incorporate for an implementation phase and a pilot study for Arizona driver’s license vision testing, clearly, there exists no all-in-one product, a panacea, that provides a wide range of automated tests to assess visual factors, diseases, and conditions that can impact driving performance. Nevertheless, it is necessary to design a system of products that merit implementation, review, and research in the Arizona Motor Vehicle Division in order to screen all drivers, and, in particular, older and at-risk drivers. The implementation phase, to follow, allows for immediate application of products that are independently tested and published and widely distributed. The B1Max™, for example, is now available for deployment after widespread distribution through the AAA Roadwise Review™ and demonstrated procedural reliability by its use as part of the DHI, the       D RIVING  H EALTH ® INVENTORY. The DHI is a tool used for driver evaluations by the Medical Advisory Board of the Maryland Motor Vehicle Administration. Additionally, the pilot study, to follow, serves to determine the effectiveness of use of the other components of the system we herein developed.

Future RAIR studies may include other variables, such as gender or race of drivers, pavement conditions, etc., in the analyses. These studies are needed in order to further identify and assess the visual abilities of various drivers and, for example, the effectiveness of certain pavement and road designs. Outreach programs may be needed.

Interestingly, the ESRA Vision Assessment Procedure for Transportation™ (ESRA VAPT™) complements the vision testing component of the NHTSA “Model Driver Screening and Evaluation Program”(Staplin et al., 2003a) for a fitness to drive determination. For example, the vision testing component of the NHTSA Model measures near and far acuity, contrast sensitivity, and visual field loss testing. The ESRA Dynamic Vision Assessment for Transportation™ (ESRA DVAT™) (Figure 7), as envisaged, provides a fully automated, comprehensive, and cost-effective approach through the testing of vision function, vision condition, and vision status. It expands and improves existing technology. The vision function element of the ESRA system includes high- and low-contrast visual acuity screening measures. The vision condition element covers the visual field and, more specifically, the detecting of eye diseases and injuries that may adversely impact driving abilities. The vision status element screens at-risk drivers and drivers age 50 years and older for dementia and other conditions that are associated with visual difficulties yet cannot be detected through contemporary vision testing techniques. It includes a driving simulator with ambient light and weather conditions.

Therefore, ADOT may provide a model for license testing improvements for all other states, countries, and agencies to follow if the ESRA Vision Assessment Procedure for Transportation™ (ESRA VAPT™) (Figure 6), the ESRA Dynamic Vision Assessment for Transportation™ (ESRA DVAT™) (Figure 7), and the ESRA Dynamic Assessment for Transportation ™ (ESRA DAT™) (Figure 8) are implemented as a pilot test and, ultimately, a statewide system.

RECOMMENDATIONS

Vision Screening System

The literature, surveys, and data analyses confirm the need for a comprehensive and automated system of vision screening. According to Ball (2003), full and comprehensive computerized and automated vision testing systems at driver’s license bureaus may significantly reduce dishonorable test-taking practices (through memorization), personnel time, and transcription errors, among other limitations. Based on our review, we suggest that Arizona take the following steps:

We recommend the following such tests, as part of the ESRA DVAT™ system:

Product Name

Useful Features

B1Max™ VACS test for vision function

• Fully automated and fast. • high- and low- contrast visual acuity screen. • ready for implementation. • widespread usage.

Systems Technology, Inc. Driving Simulators STISIM Drive™ Model E-01 (1-screen model with cab) STISIM Drive™ Model E-02 (1-screen desktop model) STISIM Drive™ Model E-03 (3-screen model with cab) STISIM Drive™ Model E-04 (3-screen desktop model) test for vision status

• pilot study test for eye status and/ or strategy through ambient light and weather conditions and to screen novice drivers, older drivers, and at-risk drivers.

Modified 3-D Amsler Grid Test test for vision condition

• pilot study test for possible visual diseases, injuries, and tumors that may impair driving abilities.

In addition to some refinements needed prior to emplacement for a pilot study, it is necessary to also ensure that the ESRA DVAT™ products provide instant scoring, short and effective on-site testing, and computer automation score reports linked by network to the driver’s license bureau. These changes are needed in order to ensure a smooth transition for the driver’s license bureau officials and to reduce the amount of paperwork and costs that may be associated with this unusual pilot study. Long queues account for many complaints at driver’s license offices (Man, 2005). The testing should be done as effectively and as swiftly as possible, without compromising thoroughness. This will reduce the issue of simulator sickness and aftereffects that some perceive as an impediment to driving simulators.

However, the issue of aftereffects, especially of the flashback effect, is of concern. The flashback effect, when flash images or flashbacks appear, following driving simulator usage, need to be explored due to safety concerns, among others, of drivers prior to implementation in any driver’s license bureau, transportation agency, or medical facility setting. These flashback effects may be delayed and occur while driving. No independent testings of the ESRA DVAT ™ System and ESRA DAT™, such as the products we identify were conducted to study for safety concerns. To the best of our knowledge, no driving simulators exist in any driver’s license bureaus we reviewed. These systems developed by ESRA are new and revolutionary. The potential benefits may be great if carefully instituted. We therefore highlight the following:

·       A driving simulator, particularly one equipped with tests of ambient light and / or weather conditions, may also assist in identification and evaluation of possible dementia drivers and drivers with varying forms of AD who, typically, would not be detected using conventional vision testing methods. Such screening methods are imperative when the number of dementia cases is expected to increase 400% over he next twenty years (Whitmer et al., 2005).

·       Driving simulators may either be used as a supplementary vision screening device or an educational tool to expose novice drivers to weather conditions for which they lack experience and put themselves at risk.

·       ADOT may select from the 1-screen cab, 3-screen cab, 1-screen desktop, and/ or 3-screen desktop models of simulators depending on cost, space considerations, and risk. (As discussed, the 3-screen models require additional expense and space. Although they may also account for a greater susceptibility to simulator sickness and possible aftereffects, they also provide a more realistic view of driving.)

·       According to our RAIR analyses, both Arizona and Florida, drivers age 16 to 19 years, ages 80 to 89 years, and age 90 years and older are most likely at fault in angle, backing, head-on, left-turn, rear-end, and sideswipe manners of collision, in clear weather, cloudy weather, rain, fog, daylight, dawn or dusk, and darkness conditions, and due to restrictions based on visual defects. These trends tend to follow bathtub-shaped curves. On average, we find that the older age groups (ages 80 years and older) are about twice as likely as the teenage drivers to be at-fault in these collisions.

·       Our RAIR results support the findings of Stamatiadis and Deacon (1995): Older drivers are more unsafe than younger drivers who, in turn, are more unsafe than middle-aged drivers.

Cognition Test

We recommend the Useful Field of View (UFOV®), a cognitive test of visual attention performed and scored on a computer. As a fully automated test, it has the potential to assist licensing authorities in the recertification process of impaired drivers. It may be used as a pre-recovery assessment of patients with head injuries to predict their driving ability. The UFOV is shown to adequately predict driving performance on the low fidelity simulation task. The UFOV is widely distributed through the AAA Roadwise Review™, where it provides a rapid and effective measure of visual information processing speed in approximately five minutes. According to Staplin (2005), the UFOV also classifies performance according to the level of functional deficit, if any, and identifies examinees whose performance is associated with a significant increase in collision risk. Following thousands of test administrations, the UFOV reliably identifies mild and serious deficits in visual attention and visual information processing speed. Therefore, the UFOV may also serve as a useful method of identifying at-risk drivers that may not be easily screened through other techniques, especially in the absence of driving simulators.

• We recommend the following such test as part of the ESRA DAT™ system:

Product Name Useful Features

Useful Field of View (U FOV®)

·       Fully automated and fast.

·       Measures visual information processing speed and visual attention.

·       Ready for implementation.

·       Demonstrated usage in MVD settings.

·       Widely distributed through AAA Roadwise Review™ as part of D RIVING H EALTH INVENTORY ®.

Knowledge Test

The knowledge test is commonly referred to as the written test. While it is now automated in many states, the knowledge test varies according to state and classifications of drivers’ licenses. It often tests the examinee’s understanding of accident prevention, pavement marking identification, safety rules, signal identification, traffic laws, traffic signage identification, and vehicle equipment.

Automated knowledge tests may allow for local and remote accessibility, multilingual features, adequate storage and record capabilities, biometrics, accommodation of individuals with various impairments, and significant reductions in dishonorable test-taking practices, among other benefits.

Ideally, these types of tests and/ or their components should be developed and based on research and published studies. For example, the ReFb-06 ™ exists as a stand-alone and fully automated sign road sign knowledge test. It is based on research sponsored by federal and state DOTs. According to Staplin (2005), this research includes identification of the most frequent and serious collision types, the problem driving behaviors associated with these collisions, and the extent to which these driving errors could reasonably be linked to a specific knowledge deficiency. The ReFb-06 ™ is a significant improvement over traditional road sign knowledge tests that most states utilize to test examinees according to the literal meaning of signs. Questions on the ReFb-06 ™ address the driving behavior that should or must be performed to safely respond to the road or traffic conditions that would lead a highway authority to install the sign in the first place.

Driving Test

The driving test allows examinees to actually drive a motor vehicle in order to demonstrate the ability to safely operate a motor vehicle. Driving tests vary for different classifications of drivers’ licenses. Since these types of tests may also differ between states, it may be necessary to eventually federalize such procedures if a federal driver’s license is adopted.

Any standardization of driving tests may incorporate elements of simulation to test the different terrain, pavement conditions, weather conditions, and sinage that drivers may encounter during intrastate and interstate travel.

While there are many good driving simulators in use and numerous simulation projects underway, we are now unable to identify any automated driving tests that can replace the actual driving tests. Safety, simulator sickness, and aftereffects associated with driving simulators require further research to explore this possibility as gas prices increase and driver’s license bureaus are burdened with staffing matters and motor vehicle maintenance costs.

Long queues at driver’s license bureaus are also an issue. Also, some driver’s license bureau officials express concerns about their safety and the safety of the examinee when conducting on-road driving tests.

In the future, automated driving simulators, as illustrated in Figure 8, may therefore provide cost-effective, quick, and “environmentally friendly” methods of conducting and/ or supplementing traditional on-road driver’s license tests, with little or no staff intervention, once all important safety concerns are adequately researched and addressed.

Driver’s License Renewal

The existing vision testing methodology at the Arizona Motor Vehicle Division should be augmented to include driver’s license renewal policy modifications and Internet-based technology to allow for testing at remote and expanded locations.

The Wearout Period of a bathtub curve, a period of increased decline, tends to initiate within the Arizona and Florida driver cohorts ages 50 to 59 years. The RAIR results, in conjunction with other preceding visual impairment studies conducted on various populations, suggest that driver’s license renewal policies also need to be modified in order to screen drivers as soon as they reach the age of 50 years. Compulsory vision testing in increments of two-year renewal periods between ages 50 to 59 years and annual vision testing for drivers age 70 years and older are now needed. Since novice drivers from ages 15 to 19 years are also susceptible to at-fault automobile collisions, they, too, require frequent vision testing, perhaps in two-year intervals. A driving simulator equipped with ambient light and weather conditions to assess the vision status of drivers, as illustrated in the ESRA DVAT™, may prove beneficial to novice drivers since many collisions among younger drivers occur in poor weather when visibility decreases and driving risk increases. These drivers tend to lack the driver vision experience that older and more seasoned drivers seem to develop.

We also suggest the following provisions for the pilot test:

·       The implementation phase should proceed for a period of five years to maximize cost-effectiveness of the ESRA DVAT™.

·       A pilot test study should commence for a period of at least two years in order to maximize the number of licensees.

·       Results should be compared to risk analyses, RAIR values, and rates of collisions, injuries, and fatalities as illustrated in this study.

·       To facilitate future studies, it is necessary to suggest a national and international database where various forms of collision data can easily and readily be accessed for analysis and review for all government agencies and industries. These would encourage further studies and contribute to areas where there is now very little.

·       The development of a new and comprehensive vision standard is now needed since the Snellen visual acuity standard is inadequate. This may be accomplished with the assistance of a panelist or representative of the International Council of Ophthalmology.

·       We suggest the driver’s license bureau decide on a maximum time allocation per test, a management and database setup for each test, and a comprehensive method of scoring and assessment to accurately screen at-risk drivers.

·       A pilot test will be necessary to validate the results of our system. Driver collision, injury, and fatality data will need to be monitored. Validation of results will not only demonstrate possible effects on safety, but also gauge the effectiveness of our innovative system as an alternative to current driver’s license testing methods within the State of Arizona and elsewhere.

Baggett (2003) recommended the use of on-road tests tailored to the needs of older drivers, at-risk drivers, or drivers of any age, especially at the time of driver’s license renewal. However, these on-road tests may involve additional motor vehicle purchases, maintenance and fuel costs, and extra staffing issues. Nevertheless, driving simulator products, such as those available through Systems Technology, Inc., with a history of independent studies on older drivers, novice drivers, and at-risk drivers, may suit the dual purpose of vision status assessment through the driver’s responses to environmental and lighting conditions, as well as, per Baggett’s recommendation, motor vehicle navigation and movement. This may prove to be a cost-effective strategy that can be used as parts of the vision and driving test methodologies once all safety concerns are addressed. However, the subject of driving simulator safety issues, as these relate to tests, such as the on-road test, is beyond the scope of this study. We, nevertheless, call for research and safety testing into these areas, among others, prior to installation and implementation in any agency.

Additional Recommendations

Vision testing research, policies, practices, and systems are in dire need of improvement in the State of Arizona and elsewhere. We therefore recommend the following:

·       The formation of a task force, led by both the Arizona Motor Vehicle Division and other ADOT officials to include representatives of various agencies: American Association for Retired Persons (AARP), AAMVA, American Automobile Association (AAA), Arizona Department of Economic Security Aging and Adult Administration, Alzheimer’s Association (Desert Southwest Chapter), Arizona Department of Health Services, Arizona Governor's Advisory Council on Aging, Parkinson’s Association, NHTSA, United States Administration on Aging, the American Medical Association, and a member of a major Ophthalomologic Organization (e.g., International Council of Ophthalmology).

·       A possible partnering with the Florida At-Risk Driving Council, a group formed in response to recent modifications in Florida driver’s license policy procedures, may also prove useful, especially through video-conferencing capabilities. The results and findings of our study may also support initiatives of the Florida At-Risk Driver Council, especially as these relate to possible vision pilot tests, policies, and procedures.

·       A possible partnering with the Florida At-Risk Driving Council may also assist ADOT in the development of further studies to explore and implement alternative forms of transportation to accommodate at-risk and older drivers who are unable to drive.

·       Due to differences in categorization of data between states, a uniform system, such as the State Data System underway at NHTSA, for comprehensively reporting collision data as well as an open database for retrieving this data, is now recommended. Ultimately, it may prove beneficial to link this data with other countries to improve collision analyses.

·       We recommend new and uniform federal visual standards and vision tests in all

·                        U.S. states. This way, a completely automated system can be used to identify all drivers, irrespective of their residency. This would simplify the licensure process and ultimately reduce a lot of paperwork and bureaucracy. Federal visual standards would also eliminate the number of drivers who may not visually qualify for a driver’s license in one state from obtaining a license in another state. Federal visual standards support similar recommendations as these relate to driver's licenses and other documents introduced through The 9/11 Commission Report (2004) (by The 9/11 Commission Report Implementation Act of 2004, S.2774) and The Intelligence Reform Bill. Arizona Senator John McCain and his cosponsors introduced this bill in the United States Senate on September 16, 2004. The Intelligence Reform Bill, signed into law by President Bush, December 17, 2004, requires federal agencies to implement uniform driver’s license issuance standards for the U.S. States. H.R. 418 (February 8, 2005) allows for the bill “…. to establish and rapidly implement regulations for State driver's license and identification document security standards…”

·       The Congress should ensure privacy and protection of personal data associated with federal driver’s licenses. This may be accomplished through sufficient backup copies, encryption, and automation techniques, among other methodologies.

·       The ESRA DAT™, ESRA DVAT™, ESRA VAPT™, and vision testing standards may also aid in the implementation of the new national identity card scheme underway in the UK, and, ultimately, may promote compatible standards across the European Union, Australia, and New Zealand. The incorporation of biometrics, such as facial recognition, fingerprints, or iris scans as planned in the UK card scheme (United Kingdom Home Office, November 2003) may actually facilitate the use of web-based automated vision testing at private homes and in other public locations other than a driver’s license bureau office or other transportation facility where licenses are issued. Other countries as well as the United States should explore these types of vision testing opportunities.

·       We recommend the automation of data and information between other transportation agencies. These measures may ultimately result in significant cost-savings, especially through the avoidance of repeatability of certain vision and cognition tests. Such assessments allow for extensive transportation applications.

·       The ESRA VAPT™ , ESRA DVAT™, and ESRA DAT™, can be optimized to incorporate other features, such as biometrics. However, these tests need to be solicited separately rather than as part of the automated vision test process to ensure compatibility with our ESRA patents-pending systems and methodologies.

·       The ESRA VAPT™, ESRA DVAT™, and ESRA DAT™, can also be optimized to incorporate multilingual capabilities.

·       Networking capabilities are essential for any products incorporated in the ESRA DAVT™, ESRA VAPT™, and ESRA DAT™, to ensure automation and ease for agencies.

·       Automation and networking of personal information between driver’s license bureaus, as recommended, will promote the use of encryption and reduce the possibility of identity theft, such the recent robbery of private data of 8,737

·       people at the Department of Motor Vehicles office in Las Vegas, Nevada (MSNBC, 2005). The stolen data included Social Security numbers, signatures and pictures of residents, in addition to blank licenses and license-making equipment.

·       This study also demonstrates support for more stringent federal standards for vision testing for commercial driver’s licenses. The potential for disaster is particularly greatest among drivers of hazardous materials cargoes. There are more than 800,000 of these shipments on our nation’s roads each day.

·       The Federal Motor Carrier Safety Improvement Act now requires a new written federal test on rider management, railroad crossing safety, and emergency evacuations for school bus drivers. By Oct. 1, 2005, all school bus drivers must have a new "S" endorsement, for school children transportation, on their commercial driver’s license (CDL). Yet, there are no comprehensive vision testing requirements in place. This issue needs to be addressed for safety purposes.

·       We therefore also recommend a pilot program to address the screening mechanisms of dementia drivers. It is possible that the ESRA DVAT™ we identify may assist in screening many different kinds of at-risk drivers, including dementia drivers. It may also allow for screening in other areas of transportation, including but not limited to aviation, rail, maritime, agriculture, and commercial driver’s license applications.

·       It would also be very useful if the State of Arizona conducted a comprehensive study on estimating the number of residents affected with dementia and, in particular, Alzheimer’s disease. An estimation of this population would assist the Motor Vehicle Division in gauging the need for certain driver’s license screening methods, tests, and policies. Other agencies would also benefit from this information through research and support services.

·       The common denominator is safety. The need for a new comprehensive and automated visual system in the State of Arizona is fundamental to reducing the high collision, injury, and fatality rates. This system should include the B1Max™ VACS and both the modified 3-D Amsler Grid Test and the driving simulator. In the unlikely event that there are technical, financial, or managerial problems hosting the simulator, then the State of Arizona should reconcile usage through the B1Max™ to quickly and easily provide automated visual acuity testing. Ultimately, the State of Arizona should also consider the modified 3DAGT product since, this not only has the potential to screen many at-risk drivers for visual impairments, but also for numerous diseases and conditions that traditional vision tests in driver’s license bureau settings fail to detect.

·       “Florida License On Wheels (FLOW) mobiles”, mobile driver’s license bureaus, are also a great concept to alleviate the long queues and heavy traffic at some driver’s license bureaus. While these are generally used for administrative tasks, such as identification card issuance and license renewals (FHSMV, 2004; Man, 2005), they may prove to be especially effective in providing driver’s license tests in remote areas, particularly those with limited Internet access and/ or staff shortages.

·       In the event that the State of Arizona can neither fund nor support the addition of ESRA DVAT™, in whole or in part, in their driver assessment Motor Vehicle Division curricula, then these instruments, once successfully and adequately tested for safety concerns, as discussed, including the flashback effect in driving simulators, should be included in hospitals and/ or other medical settings where physicians and/ or other licensed medical professionals can adequately assess driver’s license applicants. The ESRA DVAT™ and ESRA VAPT™, in whole or in part, may prove particularly useful, as this study demonstrates, in the assessment of at-risk drivers and others with vision diseases, vision injuries, and neurological disorders, including but not limited to dementia, Alzheimer’s disease, and Parkinson’s disease.

·       Several nationwide committees exist that address simulator sickness and aftereffects. As long as ADOT incorporates the driving simulator component of the ESRA VDAT™ into its driver’s license testing program, then they should follow authoritative guidelines or team up with such committees to ensure safety and comfort of examinees. ADOT may consider participating in the Simulator Users Group (SUG) whose members include first-rate international scholars with expertise in driving simulator usage and research. The Simulator Users Group (SUG) address topics as diverse as simulator validation, simulator standards, and Simulator Adaptation Syndrome. For example, they recommend pre- and post-driving simulator session questionnaires, which may be extremely valuable during a pilot test program involving driving simulators. The SUG intends to share detection, measurement, and mitigation Simulator Adaptation Syndrome techniques (University of Iowa, 2005).

·       The ESRA VAPT™ and ESRA DVAT™, can, at the discretion of the agency, incorporate other features, such as a written test, knowledge test, and/ or cognition skills test. These tests should also be automated and linked by a network. Discussions and illustrations of these ESRA designs are beyond the scope of this paper.

·       Although driving simulator usage poses a safety concern, it is suggested that transportation agencies and medical facilities have examinees sign waivers, indemnification, and release of liability waivers and not drive, fly, and/ or perform roof repair, and/ or operate any machinery until at least 72 hours have elapsed following a simulator test session to reduce the possibility of potential liability for any possible aftereffects, flashbacks, and/ or simulator sicknesses that some subjects may experience.

·       It is important to urge these agencies to implement driving simulators, such as the STISIM models we identify, with long histories of success, implementation, safety testing, and usage as these relate to both novice and older drivers. These should be documented through numerous independent and peer-reviewed publications over the last ten years in several different subject areas.

·       We strongly recommend that transportation agencies and medical facilities have examinees sign waivers, indemnification, and release of liability waivers and not drive, fly, and/ or perform roof repair, and/ or operate any machinery following all other automated forms of testing. Since these may not incorporate simulation,

and the effects, if any, may be very short, a team of independent physicians and

scientists should determine the appropriate amount of time to refrain from such

activities.

·       Transportation may need to be arranged for driving simulator and/ or other automated testing testees due to possible simulator sickness and aftereffects.

·       During the pilot test, the Simulator Sickness Questionnaire (SSQ), as developed by Kennedy et al. should be administered to testees to gauge the incidence and impacts of possible simulator sickness and aftereffects.

·       Future studies need to consider the implications of vision testing on racial groups, in particular, Asians, and Native Americans. Most scientific studies reviewed in this study focused primarily on Caucasians, African-Americans, and Hispanics. In the United States, there now exists a burgeoning population of Asians that may constitute the fastest-growing major population over the next 50 years. By 2010, this population may increase to 14 million and by 2050, this population may top 33 million (Associated Press, 2004). Many of these Asians may comprise a significant population of large U.S. cities, including Phoenix. Native Americans, per contra, may live on pueblos and reservations in rural areas where advanced vision testing facilities are scarce. In order to meet the demand of our ever-growing states and nation, driver’s license bureaus now need to consider research and testing improvements in order to adequately screen a cross-section of the U.S. society.

This study shows that safety issues associated with any new driver’s license testing system must be addressed prior to any implementation in any driver’s license bureau, transportation agency, or medical facility setting. Driving simulator studies, in particular, must cover investigations into simulator sickness, flashbacks, and successful testing techniques of the products we identify. Space constraints in a driver’s license bureau setting must also be considered due to excess heat concerns, electrical needs, lighting requirements, and crowded conditions, especially in warmer climates. Specially designed cooling systems or larger space areas may be also needed before any driving simulators are emplaced in a driver’s license bureau location. Most Florida Department of Highway Safety and Motor Vehicle driver’s license testing centers are, for example, located in small and leased storefront areas. New and specially designed buildings or equipped locations may therefore be needed to accommodate the use of driving simulators and the special needs of the testees.

Once adequate safety issues are addressed and technical modifications are made, as determined by an independent panel of physicians and scientists, as prescribed in this report, then driving simulators may offer the potential for more comprehensive and automated vision testing of older, and, possibly, novice drivers. Although a driving simulator study is beyond the scope of the original visual acuity report, our identification of driving simulator products necessitate a pilot study to explore these safety concerns and others prior to any implementation, especially as these relate to applications within the ESRA DAT™ and/ or ESRA DVAT™. (The original title of this report was “SPR

559: Comprehensive Automated Driver’s License Testing System: The Visual Acuity Test (Phase 1: Pre-Pilot Test)”. Since ESRA was unable to identify a visual acuity test that was comprehensive for driver’s license testing, we found it was advisable for ESRA to independently and entirely develop completely new and automated systems and procedures capable of thorough screening for transportation licenses and applications.) However, in the event that a driving simulator cannot be emplaced in a driver’s license agency setting due to safety, management, and/ or ergonomic issues, then the ESRA DVAT ™ System will be considered adequate with only the B1Max ™ VACS, a high- and low- contrast visual acuity screen, and ultimately, the Modified 3DAGT according to modifications outlined by and developed with the assistance of ESRA Consulting Corporation.

Our findings underscore the significance of vision measures other than standard acuity for assessing at-risk drivers and, in particular, older drivers. Due to the high collision, injury, and fatality rates of all drivers in the State of Arizona, and the disproportionate number of at-fault older drivers in the States of Arizona and Florida, new vision screening methodologies and standards are urgently needed to promote road safety, predict visual impairment, and evaluate possible restriction or confiscation of driver’s licenses. Automation techniques of other components of the driver’s license test, such as the ESRA DAT™, as we identify, should also be explored. The results of our study, which spanned an 11-year period, not only apply to Arizona and Florida, two states with some of the largest populations of older individuals in the United States, but, as our global survey demonstrated, any state, country, province, territory, or commonwealth with an increasing number of older drivers.

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Figure 6. ESRA Vision Assessment Procedure for Transportation (ESRA VAPT™)

·       At a minimum, ADOT should employ the B1Max ™ VACS, a fully automated visual acuity and contrast sensitivity screening test. This test powers the Roadwise Review™ home-based assessment tool released by AAA in January 2005. The reliability of this procedure is demonstrated by its use as part of the          D RIVING  H EALTH ® INVENTORY (D H I), which is used for driver evaluations by the Medical Advisory Board of the Maryland Motor Vehicle Administration. It provides a quick and useful screening measure of visual deficiencies that can potentially put an end to mechanical failures and long queues associated with existing vision screening techniques in transportation licensing agencies and medical facilities.

·       While automated vision function testing methodology is needed, so is a new comprehensive system, including an automated vision condition test and, a driving simulator, to adequately screen the vision of driver’s license applicants and renewals.

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Figure 7. ESRA Dynamic Vision Assessment for Transportation (ESRA DVAT ™)

Ultimately, all other parts of the driver’s license test should be considered for automation, as illustrated in Figure 8., ESRA Dynamic Assessment for Transportation (ESRA DAT ™), once adequate safety concerns are addressed.

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Figure 8. ESRA Dynamic Assessment for Transportation (ESRA DAT ™)

Although Figure 7 illustrates the vision function test and vision condition test as two separate tests, this configuration, as part of the comprehensive and automated vision testing system developed by ESRA, may be combined into one test because the B1Max ™ VACS is available as a software product. This product provides quick and reliable PC-based administration on local and networked systems and in diverse operating systems.

The ESRA Vision Assessment Procedure for Transportation™ (ESRA VAPT™) (Figure 6) and the ESRA Dynamic Vision Assessment for Transportation™ (ESRA DVAT ™) System (Figure 7) allow ADOT to validate the use of new and improved vision testing technology through a full-scale study. The ESRA Dynamic Assessment for Transportation™ (ESRA DAT™) (Figure 8) also merits further consideration, especially with the availability of the cognition tests (UFOV) and ReFb-06 ™ Road Sign Knowledge Tests. The results of such studies, as demonstrated through our global survey, stand to not only benefit drivers and driver’s license bureau officials in Arizona and elsewhere, but to also benefit transportation personnel in many other agencies as well. Hence the automation of data and information between other transportation agencies may ultimately result in significant cost-savings, especially through the avoidance of repeatability of the ESRA Dynamic Vision Assessment for Transportation™ (ESRA DVAT™) and vision attention/ cognition tests, which provide broad transportation applications.

Implementation

As this study has shown further safety gains could be achieved by more substantial improvements to the current testing methodology. The ESRA Dynamic Vision Assessment for Drivers (DVAT ™) is envisaged as a fully automated system that rigorously screens vision function, condition, and status of drivers. These include eye diseases and neuropsychologic and neuromotor disorders such as dementia. Recent studies indicate that many drivers are unaware that they have these conditions. Given the more limited option, we prescribe the ESRA DVAT ™ to significantly reduce statewide motor vehicle collisions, fatalities, and injuries.

Therefore, ESRA DVAT ™ justification can be accomplished through a system of evaluating the anticipated safety gains and collisions avoided. The estimated costs and benefits for a five-year period in approximately 50 Arizona Motor Vehicle Division offices can be quantified as follows: 

Component

Five Year Cost

Annualized Cost

Visual Acuity Test

$6,875,000

$1,375,000

Eye Condition Test

$2,500,000

$500,000

Driving Simulators

$2,750,000

$550,000

Contingency

$4,243,750

$848,750

Total*

$16,368,750

$3,273,750

* These itemized costs were conservatively calculated on the basis of a range of estimates provided to ESRA by different manufacturers. The prices for all products are subject to change and may be considerably higher if any custom or technical modifications are required.

Benefits of ESRA DVAT ™

The benefits of this improved driver testing system would be the reduction of collisions on the roadways. It is estimated that about 2 percent of drivers have serious vision or other conditions (for example, dementia) that raise their risk of collisions (National Institute of Health, 2004). Collision rates for those with diplopia are estimated to be 20 percent above average, (McCloskey et al. 1994) for glaucoma 50 percent above average (McCloskey et al. 1994) and for cataracts 150 percent above average (Owsley, et al.. 1999). Taking the lowest of these estimates as the factor for the 2 percent of impaired drivers, these drivers are projected to account for about $70 million of the annual $2.8 billion in collisions costs in Arizona. If the two-step test weeds out 80 percent of these impaired drivers (Fink, 2004) and denies them driver’s licenses, and keeps them off the roads, the benefit in terms of collision losses avoided would be about $55 million per year.

The estimated potential benefit of $45 million per year is 13 times larger than the estimated $3.3 million annualized cost of the improved testing system. The magnitude of the benefit compared to the cost creates a strong argument for pursuing a further effort to explore possible implementation of the improved test.

Granted, the benefits will not flow directly to ADOT Motor Vehicle Division in the form of funds with which to pay for implementation. Benefits will be dispersed throughout the community in the form of fewer lives lost or damaged by collisions that might have been avoided if more impaired drivers were taken off the roads. Revenues gained and costs avoided will occur in the State’s general fund. A case can be made for funding the improved driver testing procedure from these sources.

The ESRA DVAT ™ model may serve as a prototype for other states, countries, and government agencies to follow.

Note: The benefit/cost estimate was calculated by John Semmens, ADOT, from data provided by ESRA.

The ESRA DAT ™ System is developed by:

ESRA Consulting Corporation

ESRA DAT ™ Sales Division

1650 South Dixie Highway, Third Floor

Boca Raton, Florida 33432

USA

Telephone:     (561) 361-0004

Arizona Fax:  (520) 844-8555

e-mail:  dat@esracorp.com

web:      http://www.esracorp.com  

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