Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.3.2. Elder Driver Fatality Rate Projections, Males, Deaths per 100 Million Miles Driven, as Percentage of 1995 Rates National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 102.6% 98.5% 94.2% 90.4% 86.6% 83.5% 70-74 100.0% 110.4% 106.6% 102.2% 96.6% 90.8% 86.0% 75-79 100.0% 105.1% 101.1% 96.7% 92.2% 88.0% 84.3% 80-84 100.0% 85.9% 82.5% 78.7% 75.4% 72.6% 70.2% 85+ 100.0% 100.6% 92.5% 84.4% 77.3% 71.2% 66.0% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 88.2% 83.3% 78.8% 75.6% 72.4% 69.7% 70-74 100.0% 105.4% 101.8% 97.3% 92.2% 87.1% 82.9% 75-79 100.0% 100.9% 98.2% 95.0% 91.4% 87.9% 84.8% 80-84 100.0% 71.8% 69.3% 65.7% 63.2% 61.3% 59.7% 85+ 100.0% 92.5% 86.5% 80.3% 74.7% 69.9% 66.0% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 114.7% 109.1% 104.1% 99.8% 95.9% 92.6% 70-74 100.0% 85.0% 81.6% 78.3% 74.3% 70.5% 67.3% 75-79 100.0% 95.9% 92.3% 89.1% 85.4% 82.0% 79.1% 80-84 100.0% 99.0% 95.8% 91.4% 88.0% 85.2% 82.8% 85+ 100.0% 105.0% 98.5% 91.9% 85.8% 80.5% 76.1% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 115.1% 110.8% 105.6% 101.3% 96.9% 93.4% 70-74 100.0% 123.8% 118.3% 112.8% 105.8% 98.7% 93.0% 75-79 100.0% 111.7% 106.1% 99.8% 94.4% 89.6% 85.4% 80-84 100.0% 63.0% 59.6% 56.4% 53.2% 50.6% 48.3% 85+ 100.0% 93.5% 87.3% 80.7% 74.7% 69.6% 65.4% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 90.7% 86.9% 83.0% 79.1% 75.6% 72.6% 70-74 100.0% 112.2% 108.7% 104.1% 98.3% 92.3% 87.6% 75-79 100.0% 104.9% 101.3% 96.5% 91.4% 86.6% 82.4% 80-84 100.0% 94.5% 91.0% 86.9% 83.4% 80.5% 78.0% 85+ 100.0% 103.6% 85.2% 69.4% 56.0% 45.0% 36.6% GM Project G.6 A - 10 October 2000
Table A.3.3. Elder Driver Fatality Rate Projections, Females, Deaths per 100 Million Miles Driven National 1995 2000 2005 2010 2015 2020 2025 65-69 1.24 1.37 1.32 1.26 1.20 1.14 1.09 70-74 2.49 2.01 1.92 1.83 1.73 1.63 1.54 75-79 4.35 3.64 3.54 3.42 3.28 3.14 3.03 80-84 7.22 7.40 7.16 6.85 6.55 6.26 6.00 85+ 16.23 15.43 14.43 13.33 12.32 11.42 10.70 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 1.26 1.16 1.12 1.07 1.01 0.95 0.91 70-74 2.27 1.73 1.67 1.59 1.50 1.42 1.35 75-79 4.97 3.17 3.11 3.00 2.89 2.79 2.70 80-84 6.85 6.54 6.30 6.04 5.75 5.49 5.27 85+ 22.07 17.31 16.36 15.34 14.22 13.17 12.33 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 1.04 1.12 1.08 1.03 0.98 0.94 0.90 70-74 2.23 1.68 1.61 1.52 1.44 1.35 1.28 75-79 3.36 3.02 2.91 2.79 2.68 2.57 2.49 80-84 5.59 5.42 5.25 5.08 4.88 4.69 4.53 85+ 28.34 17.15 16.08 14.83 13.79 12.92 12.23 South 1995 2000 2005 2010 2015 2020 2025 65-69 1.54 1.74 1.68 1.60 1.52 1.44 1.37 70-74 2.74 2.50 2.37 2.24 2.10 1.96 1.85 75-79 5.99 4.60 4.44 4.23 4.02 3.83 3.68 80-84 8.93 9.68 9.23 8.69 8.21 7.82 7.48 85+ 15.22 16.03 14.85 13.63 12.54 11.63 10.90 West 1995 2000 2005 2010 2015 2020 2025 65-69 0.91 1.17 1.10 1.04 0.99 0.93 0.88 70-74 2.54 1.75 1.68 1.59 1.52 1.43 1.37 75-79 2.52 3.11 3.03 2.94 2.82 2.70 2.60 80-84 6.32 6.59 6.40 6.18 5.86 5.52 5.24 85+ 10.16 9.51 9.18 8.71 8.23 7.74 7.36 GM Project G.6 A - 11 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
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have a regular pattern over the age
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Table 8.2. Total Risk Crash Rate Re
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projection the asymptotic behavior
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percentages of people driving, and
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9.1.1 Computations The projection o
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Figure 9.2, the combination of thes
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Table 9.1. Sensitivity of Total Dri
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material, dampening effect on drive
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Page 142 and 143: Age group Table 9.6. Sensitivity of
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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
Page 188 and 189: Table A.2.4. Projections of Drivers
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
Page 220: 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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