Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.4.2. Projected Elderly Driver Fatalities, Males, Total Number of Fatalities as Percent of 1995 Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 106.7% 118.5% 148.5% 195.9% 230.3% 266.6% 70-74 100.0% 114.0% 111.9% 123.1% 151.5% 194.9% 225.3% 75-79 100.0% 140.9% 147.4% 147.8% 164.6% 207.8% 275.6% 80-84 100.0% 139.9% 170.6% 185.2% 192.6% 225.0% 295.2% 85+ 100.0% 128.9% 153.7% 183.2% 204.4% 213.1% 239.7% Total 100.0% 124.7% 137.3% 153.6% 179.3% 214.0% 260.7% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 92.0% 96.5% 115.3% 148.8% 174.0% 197.3% 70-74 100.0% 99.3% 96.7% 102.0% 120.2% 151.8% 174.8% 75-79 100.0% 117.8% 123.8% 123.8% 133.4% 162.3% 212.5% 80-84 100.0% 117.6% 140.3% 151.7% 156.0% 175.5% 221.0% 85+ 100.0% 115.8% 135.6% 158.4% 174.9% 181.0% 200.1% Total 100.0% 107.0% 115.9% 126.9% 144.2% 167.9% 200.3% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 110.5% 114.0% 137.4% 173.8% 197.6% 227.3% 70-74 100.0% 94.2% 85.4% 88.0% 105.2% 130.9% 147.1% 75-79 100.0% 132.9% 135.0% 125.8% 131.8% 161.5% 207.3% 80-84 100.0% 153.8% 183.0% 194.4% 189.1% 209.7% 269.2% 85+ 100.0% 188.0% 225.2% 269.5% 300.9% 306.1% 335.7% Total 100.0% 127.4% 135.5% 145.7% 161.6% 184.6% 219.6% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 118.6% 135.1% 172.0% 229.0% 269.7% 314.1% 70-74 100.0% 134.2% 134.8% 151.0% 188.5% 244.4% 282.6% 75-79 100.0% 164.1% 173.6% 176.9% 199.7% 254.6% 339.4% 80-84 100.0% 147.0% 182.5% 201.2% 214.2% 255.2% 340.7% 85+ 100.0% 113.3% 142.4% 179.1% 209.3% 228.3% 267.7% Total 100.0% 136.2% 153.0% 174.8% 208.6% 252.7% 311.3% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 95.4% 111.7% 145.0% 195.6% 234.7% 273.4% 70-74 100.0% 109.7% 109.0% 125.3% 158.8% 208.2% 245.0% 75-79 100.0% 123.1% 127.1% 129.3% 150.4% 194.8% 263.3% 80-84 100.0% 147.2% 180.6% 193.2% 202.4% 244.3% 326.0% 85+ 100.0% 147.5% 158.4% 167.6% 163.7% 150.6% 151.4% Total 100.0% 120.2% 131.8% 147.4% 173.6% 210.9% 258.9% GM Project G.6 A - 14 October 2000
Table A.4.3. Projected Elderly Driver Fatalities, Females, Total Number of Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 267 328 388 513 709 872 1051 70-74 358 363 371 422 540 722 869 75-79 323 357 397 418 488 645 895 80-84 229 400 514 568 596 701 927 85+ 146 247 334 438 532 596 702 Total 1323 1696 2004 2359 2864 3535 4444 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 68 61 71 90 122 149 177 70-74 81 78 77 85 103 134 158 75-79 92 74 81 83 94 118 159 80-84 50 82 98 104 104 116 146 85+ 35 57 77 97 115 125 143 Total 326 352 403 459 537 643 784 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 37 39 42 53 69 81 96 70-74 60 58 53 56 69 88 102 75-79 45 58 58 54 57 71 93 80-84 33 58 69 72 68 75 96 85+ 24 42 52 64 74 78 87 Total 199 255 275 299 337 393 474 South 1995 2000 2005 2010 2015 2020 2025 65-69 117 164 197 264 367 453 550 70-74 153 172 182 210 272 364 439 75-79 137 149 171 186 221 296 414 80-84 99 189 251 284 308 370 496 85+ 61 114 159 215 268 308 371 Total 567 787 960 1160 1436 1791 2270 West 1995 2000 2005 2010 2015 2020 2025 65-69 45 64 78 106 151 189 228 70-74 64 56 59 72 97 136 170 75-79 49 77 87 95 116 159 229 80-84 47 71 95 108 115 140 189 85+ 26 34 46 61 75 84 101 Total 231 301 366 442 554 708 917 GM Project G.6 A - 15 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
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
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 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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