Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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of entry/exit, safety, security, etc.), (2) to determine where and when and for what purposes the elderly would use transit, (3) to describe potential options for rural conditions, and (4) to develop a methodology for predicting transit success. In addition, public comment would be helpful to quantify the appeal and/or value of elderly communities that encourage pedestrian trails or “golf-cart” types of transportation within the community. Other approaches to achieving mobility and an acceptable quality of life for the elderly should also be explored. Although many of these research components have been considered in part (as noted in Section 3), there has been no attempt to consolidate all of the research into a single data repository. GM Project G.6 10 - 15 October 2000
REFERENCES Administration on Aging. 1997.Demographic Changes. U.S. Department of Health and H u m a n S e r v i c e s . W a s h i n g t o n , D . C . http://pr.aoa.dhhs.gov/aoa/stats/aging21/demography.html . Administration on Aging. 1999. Profile of Older Americans: 1999. U.S. Department of Health and Human Services. Washington, D.C. http://pr.aoa.dhhs.gov/aoa/stats/profile/. Administration on Aging. 2000. Transportation and the Elderly. U.S. Department of Health and Human Services. Washington, D.C. http://www.aoa.gov/factsheets/Transportation.html. American Health Care Association. 1997. The Nursing Home Facility Sourcebook: Facts and Trends – 1997. p. 7. American Health Care Association. 1998. “The Looming Crisis.” http://www.ahca.org/secure/nfres.htm and http://ahca.org/secure/alres.htm. American Psychological Association. 1996. “Touch-Screen Computer Program Predicts Crash Risk in Older Drivers,” APA Public Communications. http://www.apa.org/releases/drivers.html. American Psychological Association (Scott Sleek, Monitor staff). 1996. “Gauging When Drivers Are Too Old,” APA Public Communications. http://www.apa.org/monitor/sep96/drivingd.html. Asher, Cheryl Carleton. 1992. “Hedonic Analysis of Reliability and Safety for New Automobiles,” Journal of Consumer Affairs. Vol. 26, pp. 377-396. Ball, Karlene. 1997. “Attentional Problems and Older Drivers.” Alzheimer Disease and Associated Disorders. Vol. 11, Suppl. 1, pp. 42-47. Ball, Karlene, Cynthia Owsley, Beth Stalvey, Daniel L. Roenker, Michael E. Sloane, and Mark Graves. 1998. “Driving Avoidance and Functional Impairment in Older Drivers.” Accident Analysis and Prevention. Vol. 30, No. 3, pp. 313-22. Bawks, Bruce. Personal communication. Bruce.Bawks@eia.doe.gov. Becker, Gary S. 1965. “A Theory of the Allocation of Time.” Economic Journal. Vol. 75, pp. 493-517. GM Project G.6 R - 1 October 2000
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ORNL-6963 Projecting Fatalities in
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4. ANALYSIS OF DATA SETS ..........
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GM Project G.6 vi October 2000
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LIST OF TABLES Table ES-1 Elderly D
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Table A.5.3 Projected Total Fatalit
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NASS National Automotive Sampling S
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Over the past century, the numbers
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Figure ES-1. Projected Active Drive
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Table ES-1. Elderly Driver Fatality
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1. INTRODUCTION America is graying.
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of existing data bases, including h
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various data sources and their abil
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Finally, data sets should contain,
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• Examine data sources to determi
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health care, resulting in longer li
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Age group Table 3.2. Projected Rati
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that individuals will not retire at
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analysis. Distribution of the elder
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More elderly people live in rural a
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assessments of health status) does
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3.2.2 Impacts of Increasing Frailty
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current vision screening tests at d
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Number of Licenses (thousands) 100
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3.3.2 Changes in Driving Habits In
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Transportation Survey (NPTS) data,
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tourist services, and “smart” s
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Specific highway enhancements to re
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3.4.2 Other GM Project Results (Pro
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• As age increased, being struck
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men using mid-1990s data, this gend
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major contributing factor as was dr
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Total (percent) 100 80 60 40 20 0 A
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cohort behavior and conditions for
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4.2.3 Drivers and Driving Distance
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The HRS and the AHEAD studies are c
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these data and weights. Because of
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U.S. Census Bureau (http://www.cens
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5. OVERVIEW OF THE MODELING SYSTEM
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or acquisition costs, of the goods
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institutionalized settings, our pro
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elationships between health and the
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6. THE PROPORTION OF THE ELDERLY PO
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Employment status represents a deri
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statistical relationship exists bet
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more likely to be drivers if there
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Statistics (BLS) projections beyond
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considerably greater proportional c
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Table 6.3 (continued) Western Men W
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Daily Person Trips/Person Figure 7.
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Second, VMT as a consumption item i
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century on which we are unable to o
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The health status effects are posit
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significant one in the final set of
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empirically derived regression coef
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GM Project G.6 7 - 14 October 2000
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Table 7.3. Determinants of Projecte
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8. FATAL CRASH RATES 8.1 MODELING F
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The other fatality risk concept we
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dropped. Since these measures have
Page 120 and 121: have a regular pattern over the age
Page 122 and 123: Table 8.2. Total Risk Crash Rate Re
Page 124 and 125: projection the asymptotic behavior
Page 126 and 127: GM Project G.6 8 - 13 October 2000
Page 128 and 129: GM Project G.6 8 - 15 October 2000
Page 130 and 131: percentages of people driving, and
Page 132 and 133: 9.1.1 Computations The projection o
Page 134 and 135: Figure 9.2, the combination of thes
Page 136 and 137: Table 9.1. Sensitivity of Total Dri
Page 138 and 139: material, dampening effect on drive
Page 140 and 141: Table 9.2. Sensitivity of 2025 Proj
Page 142 and 143: Age group Table 9.6. Sensitivity of
Page 144 and 145: 9.3.1 The Effect of Time on VMT Pro
Page 146 and 147: Figure 9.4. Projected VMT, Women (U
Page 148 and 149: Figure 9.6. Component Contributions
Page 150 and 151: Step 1: Introduction Step 2: Decisi
Page 152 and 153: Step 3a: Modifying Income at differ
Page 154 and 155: Clicking on one of the sheet tabs w
Page 156 and 157: 10. SUMMARY, CONCLUSIONS, AND RECOM
Page 158 and 159: similarly relied on a regression mo
Page 160 and 161: trend of fatal crashes in the futur
Page 162 and 163: The base of exposure to crash risk
Page 164 and 165: population, and a slightly smaller
Page 166 and 167: Second, improvements in health stat
Page 168 and 169: projections of VMT may be high. Our
Page 172 and 173: Blincoe, Lawrence. 1994. Estimating
Page 174 and 175: College of Commerce and Business Ad
Page 176 and 177: National Association of Development
Page 178 and 179: Suen, S. Ling, C. G. B. Mitchell, a
Page 180 and 181: GLOSSARY Baby boomers Persons born
Page 182 and 183: Table A.1.2. Projections of Vehicle
Page 184 and 185: Table A.1.4. Projections of Vehicle
Page 186 and 187: Table A.2.2. Projections of Drivers
Page 188 and 189: Table A.2.4. Projections of Drivers
Page 190 and 191: Table A.3.2. Elder Driver Fatality
Page 192 and 193: Table A.3.4. Elder Driver Fatality
Page 194 and 195: Table A.4.2. Projected Elderly Driv
Page 196 and 197: Table A.4.4. Projected Elderly Driv
Page 198 and 199: Table A.5.2. Projected Total Fatali
Page 206 and 207: Table B.1. Projections of Non-Insti
Page 208 and 209: Table B.3. Projections of Non-Insti
Page 210 and 211: B.2. INDEPENDENT VARIABLES PROJECTI
Page 212 and 213: Table B.5. Male DRI Income Projecti
Page 214 and 215: B.2.1.2. Projection Adjustments to
Page 216 and 217: B.2.5 Seatbelt Use Our projections
Page 218 and 219: C.3. DECREASING GROWTH RATES OF DRI
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GM Project G.6 C - 4 October 2000 T
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Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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