Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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material, dampening effect on driver fatalities among all age groups and both genders. Many of the elasticities are of substantial magnitude, particularly among the female age groups. Improved health status has the counterintuitive effect of increasing older driver fatalities, and by substantial percentages per unit improvement in health as reported by these elasticity values. There is an equally natural intuitive understanding of this result inasmuch as people with fewer activity limitations are more likely to be mobile and thence experience greater exposure to traffic crashes. Again, this operates through both VMT and the percent of elderly that continue driving. Urban location has a small, but rather consistent, dampening effect on driver fatalities, although the magnitudes for the two oldest groups of women are considerably larger. Clearly this reflects the greater availability of substitutes for driving in cities. One can interpret these elasticities as the impact of a 1% increase in the percent of the total (or regional) population living in cities on the number of elder driver fatalities. As the projection model is structured, this effect derives strictly from the driver percentage component of exposure, without an additional channel through VMT. 1 The seat-belt-use elasticities are encouraging in that they are sizeable as well as negative. They are the same magnitude for both genders because no gender difference was detectable in the regression coefficients of seat belt use in the crash rate model. Whether this effect would survive more detailed, individual information on seat belt use by age, we cannot say, but it certainly is worth exploration. 1 Recall that the exclusion of a substitute-for-driving variable in the VMT demand equation was the consequence of data limitations in an early NPTS. Location in a SMA was not considered an adequate indicator of substitutes for VMT, and information on proximity to, or otherwise availability of, public transit was unavailable in the 1983 NPTS. Location in a SMA was considered an adequate indicator of substitutes for driving at all. GM Project G.6 9 - 8 October 2000
9.2.2 Sensitivity of the Projection Components to Individual Variables In Section 9.2.1 we noted that some independent variables worked their effects on total driver fatalities through several routes. The best example of this is income, which affects all three of the projection components constructed in this research (population growth projections, of course, being supplied by the U.S. Census Bureau). Each of the following six tables reports the sensitivity of the projections of each major component to one of the independent variables. A final column at the right of each table reports the total effect of the variable on driver fatalities. Having alluded to the differential effects of some independent variables on the separate projection components in the discussion of the sensitivity of driver fatalities, we provide no further examination of the elasticities of Tables 9.2 through 9.7. 9.3 A LOWER BOUND FOR DRIVER FATALITIES AND VMT We have noted that we believe our driver fatality projections to be as high as is reasonable, principally because the elderly VMT projections are as high as could be expected. We do not believe that annual VMT per capita will exceed the projections in Figure 7.3 and the accompanying appendix tables. The contributions of income growth and growth in elderly labor force participation are solidly established, but the time trend terms in the projection equations, as noted in Chapter 7, contribute substantial, in some age/gender groups even dominant, proportions of the growth in VMT projected to 2020. Although the empirical basis of the magnitude of the time trend coefficients is indisputably comprised of GM Project G.6 9 - 9 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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Page 92 and 93: Statistics (BLS) projections beyond
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Page 96 and 97: Table 6.3 (continued) Western Men W
Page 98 and 99: Daily Person Trips/Person Figure 7.
Page 100 and 101: Second, VMT as a consumption item i
Page 102 and 103: century on which we are unable to o
Page 104 and 105: The health status effects are posit
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Page 108 and 109: empirically derived regression coef
Page 110 and 111: GM Project G.6 7 - 14 October 2000
Page 112 and 113: Table 7.3. Determinants of Projecte
Page 114 and 115: 8. FATAL CRASH RATES 8.1 MODELING F
Page 116 and 117: The other fatality risk concept we
Page 118 and 119: 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 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 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 170 and 171: of entry/exit, safety, security, et
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
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Table A.2.4. Projections of Drivers
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Table A.3.2. Elder Driver Fatality
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Table A.3.4. Elder Driver Fatality
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Table A.4.2. Projected Elderly Driv
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Table A.4.4. Projected Elderly Driv
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Table A.5.2. Projected Total Fatali
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Table B.1. Projections of Non-Insti
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Table B.3. Projections of Non-Insti
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B.2. INDEPENDENT VARIABLES PROJECTI
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Table B.5. Male DRI Income Projecti
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B.2.1.2. Projection Adjustments to
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B.2.5 Seatbelt Use Our projections
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C.3. DECREASING GROWTH RATES OF DRI
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GM Project G.6 C - 4 October 2000 T
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