Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table 6.3 (continued) Western Men Western Women Age Income Employment Time Income Employment Time status trend status trend 65 27.70% 1.14% 71.16% 11.28% 0.17% 88.55% 70 21.68% 4.86% 73.45% 9.12% 0.48% 90.40% 75 29.98% 0.28% 69.75% 5.26% 0.10% 94.64% 80 5.78% 0.24% 93.98% 5.04% 0.13% 94.83% 85+ 2.10% 0.04% 97.87% 3.35% 0.04% 96.61% GM Project G.6 6 - 13 October 2000
1 Person miles of travel includes travel by any mode or means; VMT/person implies that the person is driving the vehicle. 7. VEHICLE MILES TRAVELED 7.1 HISTORICAL TRENDS IN ELDERLY DRIVING The total person miles of travel for all drivers in the United States increased from 2,026 billion miles in 1983 to 2,141 billion miles in 1990 to 2,663 billion miles in 1995, a total increase of 31.4% (U.S. Department of Transportation, 1997B). Historical driving trends among the elderly also show a general increase in the annual amount of VMT per person 1 (Figure 7.1). The age group of persons over 85 have seen the largest increases. Men over 85 drove an average of 1933 miles per year in 1983, a number which more than doubled to 5166 in 1995. Women also saw a sharp increase in VMT per person in that time frame, tripling their driving miles from 1828 in 1990 to 2781 miles in 1995. Insufficient VMT data for women over 85 in 1977 and for all persons over 85 in 1983 prevented us from obtaining comparisons over a longer time frame. Increases in other elderly groups were less dramatic, but still substantial, with men between the ages of 65 and 84 increasing the number of miles driven by 35%, and women in that same age group increasing their average numbers from 35% (65-74) to 75% (75-84). This increases show changes in the driving habits of older women, who are clearly driving a substantial amount more than women of similar ages in the past. However, as shown in Figure 7.1, the rate of increase for the elderly between ages 65 and 84 was greater between 1983 and 1990 than it was between 1990 and 1995. Note that statistical changes in the 1995 VMT measures of the NPTS are believed to understate actual VMT for that time period. Travel habits of the elderly are different from those of younger age groups. In 1995, the average person over 65 took fewer trips for every trip purpose than those under 65, with the most substantial decline, logically, in trips to earn a living (Figure 7.2). The smallest GM Project G.6 7 - 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
Page 46 and 47: Number of Licenses (thousands) 100
Page 48 and 49: 3.3.2 Changes in Driving Habits In
Page 50 and 51: Transportation Survey (NPTS) data,
Page 52 and 53: tourist services, and “smart” s
Page 54 and 55: Specific highway enhancements to re
Page 56 and 57: 3.4.2 Other GM Project Results (Pro
Page 58 and 59: • As age increased, being struck
Page 60 and 61: men using mid-1990s data, this gend
Page 62 and 63: major contributing factor as was dr
Page 64 and 65: Total (percent) 100 80 60 40 20 0 A
Page 66 and 67: cohort behavior and conditions for
Page 68 and 69: 4.2.3 Drivers and Driving Distance
Page 70 and 71: The HRS and the AHEAD studies are c
Page 72 and 73: these data and weights. Because of
Page 74 and 75: U.S. Census Bureau (http://www.cens
Page 76 and 77: 5. OVERVIEW OF THE MODELING SYSTEM
Page 78 and 79: or acquisition costs, of the goods
Page 80 and 81: institutionalized settings, our pro
Page 82 and 83: elationships between health and the
Page 84 and 85: 6. THE PROPORTION OF THE ELDERLY PO
Page 86 and 87: Employment status represents a deri
Page 88 and 89: statistical relationship exists bet
Page 90 and 91: more likely to be drivers if there
Page 92 and 93: Statistics (BLS) projections beyond
Page 94 and 95: considerably greater proportional c
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
Page 106 and 107: significant one in the final set of
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 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
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Figure 9.4. Projected VMT, Women (U
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Figure 9.6. Component Contributions
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Step 1: Introduction Step 2: Decisi
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Step 3a: Modifying Income at differ
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Clicking on one of the sheet tabs w
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10. SUMMARY, CONCLUSIONS, AND RECOM
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similarly relied on a regression mo
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trend of fatal crashes in the futur
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The base of exposure to crash risk
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population, and a slightly smaller
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Second, improvements in health stat
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projections of VMT may be high. Our
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of entry/exit, safety, security, et
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Blincoe, Lawrence. 1994. Estimating
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College of Commerce and Business Ad
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National Association of Development
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Suen, S. Ling, C. G. B. Mitchell, a
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GLOSSARY Baby boomers Persons born
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Table A.1.2. Projections of Vehicle
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Table A.1.4. Projections of Vehicle
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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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Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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