Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.3.4. Elder Driver Fatality Rate Projections, Females, Deaths per 100 Million Miles Driven, as Percentage of 1995 Rates National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 110.3% 106.7% 101.9% 96.8% 91.7% 87.7% 70-74 100.0% 80.6% 77.3% 73.5% 69.5% 65.3% 62.0% 75-79 100.0% 83.7% 81.5% 78.6% 75.4% 72.3% 69.6% 80-84 100.0% 102.5% 99.2% 94.9% 90.7% 86.7% 83.2% 85+ 100.0% 95.1% 88.9% 82.2% 75.9% 70.4% 65.9% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 92.0% 89.1% 84.7% 80.3% 75.8% 72.3% 70-74 100.0% 76.4% 73.5% 70.0% 66.3% 62.4% 59.4% 75-79 100.0% 63.8% 62.6% 60.4% 58.2% 56.1% 54.4% 80-84 100.0% 95.6% 92.1% 88.2% 84.0% 80.1% 76.9% 85+ 100.0% 78.4% 74.1% 69.5% 64.4% 59.7% 55.9% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 108.0% 103.9% 99.6% 95.0% 90.6% 87.0% 70-74 100.0% 75.5% 72.0% 68.1% 64.5% 60.6% 57.6% 75-79 100.0% 90.0% 86.7% 83.2% 79.9% 76.7% 74.1% 80-84 100.0% 96.9% 93.8% 90.8% 87.3% 83.9% 81.0% 85+ 100.0% 60.5% 56.7% 52.3% 48.7% 45.6% 43.2% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 112.9% 109.3% 104.2% 98.8% 93.4% 89.1% 70-74 100.0% 91.5% 86.7% 81.9% 77.0% 71.8% 67.7% 75-79 100.0% 76.8% 74.3% 70.7% 67.2% 64.0% 61.4% 80-84 100.0% 108.4% 103.4% 97.4% 92.0% 87.5% 83.8% 85+ 100.0% 105.3% 97.5% 89.5% 82.4% 76.4% 71.6% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 127.8% 120.9% 113.9% 108.1% 102.0% 97.0% 70-74 100.0% 69.0% 66.0% 62.8% 59.7% 56.4% 53.9% 75-79 100.0% 123.6% 120.3% 116.8% 112.0% 107.2% 103.2% 80-84 100.0% 104.2% 101.3% 97.7% 92.6% 87.3% 82.9% 85+ 100.0% 93.5% 90.3% 85.7% 81.0% 76.1% 72.4% GM Project G.6 A - 12 October 2000
Table A.4.1. Projected Elderly Driver Fatalities, Males, Total Number of Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 614 655 728 912 1203 1414 1637 70-74 598 682 669 736 906 1166 1347 75-79 553 779 815 817 911 1149 1524 80-84 475 664 810 880 915 1069 1402 85+ 328 423 504 601 670 699 786 Total 2568 3203 3526 3946 4605 5497 6696 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 157 144 152 181 234 273 310 70-74 147 146 142 150 177 223 257 75-79 125 147 155 155 167 203 266 80-84 131 154 184 199 204 230 289 85+ 84 97 114 133 147 152 168 Total 644 689 746 817 928 1081 1290 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 73 81 83 100 127 144 166 70-74 105 99 90 92 110 137 154 75-79 85 113 115 107 112 137 176 80-84 67 103 123 130 127 141 180 85+ 41 77 92 110 123 126 138 Total 371 473 503 540 599 685 815 South 1995 2000 2005 2010 2015 2020 2025 65-69 273 324 369 470 625 736 857 70-74 234 314 315 353 441 572 661 75-79 235 386 408 416 469 598 798 80-84 198 291 361 398 424 505 675 85+ 149 169 212 267 312 340 399 Total 1089 1484 1666 1904 2271 2752 3390 West 1995 2000 2005 2010 2015 2020 2025 65-69 111 106 124 161 217 261 303 70-74 112 123 122 140 178 233 274 75-79 108 133 137 140 162 210 284 80-84 79 116 143 153 160 193 258 85+ 54 80 86 91 88 81 82 Total 464 558 612 684 806 978 1202 GM Project G.6 A - 13 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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Table 9.2. Sensitivity of 2025 Proj
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 190 and 191: Table A.3.2. 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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