Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.6.2. Projected Total Fatalities Attributed to Male Drivers, as Percentage of 1995 Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 108.3% 122.9% 158.1% 212.7% 255.4% 301.3% 70-74 100.0% 111.1% 109.1% 120.8% 151.8% 200.1% 236.7% 75-79 100.0% 145.1% 154.9% 159.9% 183.7% 238.6% 325.5% 80-84 100.0% 142.9% 177.1% 196.9% 209.0% 247.5% 329.3% 85+ 100.0% 129.7% 155.9% 189.3% 215.4% 228.1% 261.1% Total 100.0% 124.4% 138.1% 158.2% 190.8% 234.0% 290.8% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 91.9% 99.7% 123.1% 161.7% 193.0% 223.2% 70-74 100.0% 96.0% 93.0% 98.6% 117.9% 151.6% 177.6% 75-79 100.0% 114.5% 121.0% 122.3% 134.1% 166.1% 221.5% 80-84 100.0% 147.4% 177.9% 197.7% 206.2% 233.2% 295.3% 85+ 100.0% 115.0% 136.6% 163.2% 183.9% 193.1% 216.8% Total 100.0% 109.3% 119.6% 134.0% 155.6% 184.6% 223.7% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 118.2% 125.3% 154.8% 199.4% 230.5% 269.6% 70-74 100.0% 91.5% 83.1% 85.8% 103.7% 130.9% 149.2% 75-79 100.0% 139.8% 144.5% 136.5% 146.1% 182.4% 238.4% 80-84 100.0% 156.2% 187.1% 203.2% 200.2% 223.7% 289.5% 85+ 100.0% 173.0% 209.6% 255.2% 289.7% 298.3% 331.7% Total 100.0% 125.4% 133.3% 145.6% 166.2% 194.0% 233.8% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 119.5% 138.2% 180.3% 244.5% 294.1% 349.0% 70-74 100.0% 128.6% 130.0% 146.7% 187.8% 250.7% 298.1% 75-79 100.0% 168.9% 184.2% 195.2% 228.1% 299.8% 412.0% 80-84 100.0% 121.1% 154.8% 175.8% 193.4% 236.2% 323.7% 85+ 100.0% 115.8% 148.0% 191.1% 228.9% 254.5% 304.5% Total 100.0% 132.0% 149.7% 175.8% 217.6% 271.6% 341.7% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 99.2% 118.4% 157.2% 217.3% 266.8% 317.5% 70-74 100.0% 112.3% 110.7% 127.8% 164.7% 221.0% 265.6% 75-79 100.0% 135.0% 141.3% 147.6% 177.3% 237.4% 331.1% 80-84 100.0% 176.6% 219.4% 239.6% 255.2% 311.2% 420.0% 85+ 100.0% 153.3% 161.3% 168.7% 164.5% 151.5% 152.5% Total 100.0% 126.8% 140.5% 161.1% 196.6% 246.3% 310.2% GM Project G.6 A - 22 October 2000
Table A.6.3. Projected Total Fatalities Attributed to Female Drivers, Number of Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 316 396 475 645 917 1167 1446 70-74 362 407 420 484 632 866 1067 75-79 322 350 392 419 500 676 957 80-84 196 351 451 505 537 642 865 85+ 106 179 245 328 408 465 559 Total 1302 1683 1982 2382 2995 3816 4894 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 70 75 87 114 159 202 246 70-74 80 85 84 93 115 153 184 75-79 95 73 80 83 95 122 167 80-84 45 90 108 117 119 137 175 85+ 26 43 58 75 91 101 118 Total 315 366 418 482 580 715 891 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 47 49 54 69 93 111 134 70-74 69 66 60 64 80 105 124 75-79 47 60 61 58 62 79 106 80-84 36 76 91 96 92 103 134 85+ 20 32 40 51 60 64 72 Total 218 283 307 338 387 462 570 South 1995 2000 2005 2010 2015 2020 2025 65-69 137 193 235 322 461 588 734 70-74 144 188 202 238 315 435 538 75-79 128 148 171 192 234 322 461 80-84 75 117 159 187 209 256 353 85+ 42 78 112 157 201 237 292 Total 527 724 879 1095 1420 1838 2378 West 1995 2000 2005 2010 2015 2020 2025 65-69 62 79 99 140 205 266 331 70-74 69 68 73 89 122 173 220 75-79 52 69 79 87 109 152 223 80-84 40 68 93 106 117 146 204 85+ 18 26 34 46 56 64 77 Total 241 311 378 467 607 801 1056 GM Project G.6 A - 23 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
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Age group Table 9.6. Sensitivity of
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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
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 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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