Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table B.1. Projections of Non-Institutionalized Population, Males National 1995 2000 2005 2010 2015 2020 2025 65-69 4,441,007 4,254,151 4,577,821 5,572,529 7,142,692 8,190,136 9,215,012 70-74 3,781,060 3,799,423 3,693,202 4,031,432 4,966,407 6,411,892 7,397,098 75-79 2,561,733 2,916,192 2,993,089 2,955,493 3,250,372 4,056,984 5,311,543 80-84 1,515,468 1,740,620 2,024,681 2,111,585 2,112,372 2,387,147 3,027,950 85+ 736,606 882,223 1,052,097 1,271,548 1,447,238 1,544,189 1,768,914 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 1,056,828 1,012,231 1,051,850 1,227,212 1,543,805 1,763,067 1,946,517 70-74 889,148 896,313 868,929 915,905 1,083,785 1,376,248 1,582,670 75-79 613,341 685,117 703,774 692,251 736,198 884,765 1,141,612 80-84 368,805 412,904 470,131 489,107 486,817 532,842 652,059 85+ 185,216 214,114 247,734 291,198 326,092 343,423 383,703 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 937,376 832,856 840,097 991,096 1,225,290 1,361,905 1,526,124 70-74 799,287 778,855 703,317 721,845 863,533 1,077,341 1,206,911 75-79 543,802 602,168 600,584 552,718 573,173 695,822 882,059 80-84 323,911 359,263 407,073 414,066 387,048 414,062 512,005 85+ 157,019 181,730 210,483 248,934 278,156 285,323 314,218 South 1995 2000 2005 2010 2015 2020 2025 65-69 1,570,741 1,559,096 1,723,376 2,140,123 2,777,528 3,196,122 3,624,162 70-74 1,323,734 1,362,966 1,366,806 1,526,902 1,914,550 2,497,906 2,887,473 75-79 882,080 1,026,286 1,075,154 1,090,510 1,224,072 1,552,232 2,049,929 80-84 515,898 603,928 716,442 759,509 778,238 894,740 1,150,475 85+ 246,889 300,405 361,840 442,168 508,151 549,796 638,026 West 1995 2000 2005 2010 2015 2020 2025 65-69 876,061 849,968 962,499 1,214,098 1,596,069 1,869,043 2,118,209 70-74 768,891 761,289 754,150 866,780 1,104,540 1,460,396 1,720,044 75-79 522,510 602,621 613,576 620,013 716,929 924,165 1,237,943 80-84 306,853 364,525 431,035 448,904 460,269 545,504 713,410 85+ 147,483 185,975 232,040 289,249 334,839 365,646 432,967 GM Project G.6 B - 2 October 2000
Table B.2. Projections of Non-Institutionalized Population, Males, as Percent of 1995 Population National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 95.8% 103.1% 125.5% 160.8% 184.4% 207.5% 70-74 100.0% 100.5% 97.7% 106.6% 131.3% 169.6% 195.6% 75-79 100.0% 113.8% 116.8% 115.4% 126.9% 158.4% 207.3% 80-84 100.0% 114.9% 133.6% 139.3% 139.4% 157.5% 199.8% 85+ 100.0% 119.8% 142.8% 172.6% 196.5% 209.6% 240.1% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 95.8% 99.5% 116.1% 146.1% 166.8% 184.2% 70-74 100.0% 100.8% 97.7% 103.0% 121.9% 154.8% 178.0% 75-79 100.0% 111.7% 114.7% 112.9% 120.0% 144.3% 186.1% 80-84 100.0% 112.0% 127.5% 132.6% 132.0% 144.5% 176.8% 85+ 100.0% 115.6% 133.8% 157.2% 176.1% 185.4% 207.2% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 88.8% 89.6% 105.7% 130.7% 145.3% 162.8% 70-74 100.0% 97.4% 88.0% 90.3% 108.0% 134.8% 151.0% 75-79 100.0% 110.7% 110.4% 101.6% 105.4% 128.0% 162.2% 80-84 100.0% 110.9% 125.7% 127.8% 119.5% 127.8% 158.1% 85+ 100.0% 115.7% 134.0% 158.5% 177.1% 181.7% 200.1% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 99.3% 109.7% 136.2% 176.8% 203.5% 230.7% 70-74 100.0% 103.0% 103.3% 115.3% 144.6% 188.7% 218.1% 75-79 100.0% 116.3% 121.9% 123.6% 138.8% 176.0% 232.4% 80-84 100.0% 117.1% 138.9% 147.2% 150.9% 173.4% 223.0% 85+ 100.0% 121.7% 146.6% 179.1% 205.8% 222.7% 258.4% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 97.0% 109.9% 138.6% 182.2% 213.3% 241.8% 70-74 100.0% 99.0% 98.1% 112.7% 143.7% 189.9% 223.7% 75-79 100.0% 115.3% 117.4% 118.7% 137.2% 176.9% 236.9% 80-84 100.0% 118.8% 140.5% 146.3% 150.0% 177.8% 232.5% 85+ 100.0% 126.1% 157.3% 196.1% 227.0% 247.9% 293.6% GM Project G.6 B - 3 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
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Step 3a: Modifying Income at differ
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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 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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