Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.5.4. Projected Total Fatality Rates Attributed to Female Drivers, Deaths per 100 Million Miles, as Percent of 1995 Rates National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 112.7% 110.5% 108.3% 105.9% 103.6% 101.9% 70-74 100.0% 89.5% 86.6% 83.6% 80.6% 77.6% 75.3% 75-79 100.0% 82.5% 81.0% 79.7% 78.2% 76.6% 75.3% 80-84 100.0% 106.7% 103.8% 101.0% 98.2% 95.6% 93.5% 85+ 100.0% 95.6% 90.4% 85.3% 80.6% 76.1% 72.6% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 109.6% 107.1% 104.6% 102.2% 99.9% 98.0% 70-74 100.0% 85.2% 81.9% 78.7% 75.6% 72.7% 70.4% 75-79 100.0% 61.2% 59.8% 58.6% 57.3% 56.1% 55.1% 80-84 100.0% 115.4% 112.6% 109.8% 107.0% 104.4% 102.3% 85+ 100.0% 81.4% 77.2% 73.3% 69.6% 66.1% 63.3% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 108.3% 105.8% 103.4% 101.0% 98.7% 96.9% 70-74 100.0% 74.0% 71.2% 68.4% 65.8% 63.2% 61.2% 75-79 100.0% 89.8% 87.8% 86.0% 84.1% 82.3% 80.9% 80-84 100.0% 117.3% 114.4% 111.5% 108.7% 106.0% 103.9% 85+ 100.0% 54.3% 51.6% 49.0% 46.5% 44.1% 42.3% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 113.4% 110.8% 108.2% 105.7% 103.3% 101.4% 70-74 100.0% 106.8% 102.7% 98.7% 94.9% 91.2% 88.4% 75-79 100.0% 81.1% 79.3% 77.6% 76.0% 74.3% 73.1% 80-84 100.0% 88.2% 86.0% 83.9% 81.8% 79.7% 78.1% 85+ 100.0% 104.2% 98.9% 93.9% 89.1% 84.6% 81.1% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 113.7% 111.1% 108.6% 106.1% 103.6% 101.7% 70-74 100.0% 77.6% 74.6% 71.7% 69.0% 66.3% 64.2% 75-79 100.0% 105.7% 103.5% 101.3% 99.1% 97.0% 95.3% 80-84 100.0% 119.7% 116.7% 113.8% 110.9% 108.2% 106.0% 85+ 100.0% 101.5% 96.3% 91.5% 86.8% 82.4% 79.0% GM Project G.6 A - 20 October 2000
Table A.6.1. Projected Total Fatalities Attributed to Male Drivers, Number of Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 805 871 989 1272 1711 2055 2424 70-74 733 814 800 885 1112 1467 1735 75-79 613 890 950 980 1127 1463 1996 80-84 469 670 831 924 981 1161 1545 85+ 270 351 421 512 583 617 706 Total 2890 3596 3991 4573 5513 6763 8406 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 206 189 205 253 333 397 459 70-74 175 168 163 173 207 266 311 75-79 141 161 171 172 189 234 312 80-84 126 185 223 248 259 293 371 85+ 71 81 96 115 130 136 153 Total 718 785 859 962 1117 1326 1607 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 94 111 118 146 188 217 254 70-74 129 118 107 111 134 169 192 75-79 93 130 134 127 136 169 221 80-84 61 95 114 124 122 136 176 85+ 38 66 80 97 111 114 127 Total 415 520 553 604 690 805 970 South 1995 2000 2005 2010 2015 2020 2025 65-69 345 413 477 623 844 1016 1205 70-74 286 367 371 419 536 716 851 75-79 255 430 469 497 581 763 1049 80-84 197 238 304 346 380 464 636 85+ 118 137 175 226 271 301 360 Total 1200 1585 1797 2110 2612 3260 4102 West 1995 2000 2005 2010 2015 2020 2025 65-69 159 158 189 250 346 425 506 70-74 143 161 158 183 236 316 380 75-79 125 169 176 184 222 297 414 80-84 86 152 189 206 220 268 362 85+ 43 66 70 73 71 66 66 Total 557 706 782 897 1094 1371 1727 GM Project G.6 A - 21 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
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 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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