Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.4.4. Projected Elderly Driver Fatalities, Females, Total Number of Fatalities as Percent of 1995 Fatalities National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 122.9% 145.3% 192.1% 265.4% 326.7% 393.6% 70-74 100.0% 101.5% 103.6% 117.9% 150.9% 201.6% 242.8% 75-79 100.0% 110.6% 122.9% 129.3% 150.9% 199.5% 277.0% 80-84 100.0% 174.6% 224.5% 248.1% 260.3% 306.0% 404.9% 85+ 100.0% 169.0% 228.6% 300.0% 364.2% 407.9% 481.0% Total 100.0% 128.2% 151.5% 178.3% 216.5% 267.2% 335.9% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 89.6% 103.8% 132.1% 179.4% 219.7% 260.4% 70-74 100.0% 95.7% 95.2% 104.4% 127.0% 164.9% 195.3% 75-79 100.0% 80.1% 87.9% 90.1% 101.7% 128.2% 173.3% 80-84 100.0% 164.4% 196.4% 207.8% 207.7% 232.6% 291.1% 85+ 100.0% 164.2% 219.4% 278.4% 328.8% 358.0% 409.6% Total 100.0% 107.9% 123.8% 140.7% 164.8% 197.1% 240.4% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 106.2% 113.6% 142.7% 187.2% 219.9% 259.3% 70-74 100.0% 97.1% 88.3% 92.8% 114.4% 146.7% 169.8% 75-79 100.0% 128.2% 129.3% 118.9% 125.9% 157.5% 206.6% 80-84 100.0% 175.9% 209.6% 219.0% 207.4% 227.5% 291.5% 85+ 100.0% 173.6% 217.4% 267.7% 308.7% 323.8% 360.8% Total 100.0% 128.1% 138.0% 150.0% 169.4% 197.5% 238.0% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 140.0% 168.5% 225.8% 313.5% 387.2% 470.1% 70-74 100.0% 112.2% 118.6% 137.2% 177.7% 238.1% 286.7% 75-79 100.0% 109.1% 124.9% 136.1% 161.5% 216.3% 302.0% 80-84 100.0% 190.9% 253.8% 287.2% 311.5% 373.3% 501.4% 85+ 100.0% 186.3% 260.4% 352.9% 439.3% 505.1% 608.4% Total 100.0% 138.9% 169.3% 204.6% 253.3% 315.9% 400.3% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 142.6% 173.5% 235.9% 334.5% 419.0% 506.6% 70-74 100.0% 87.2% 92.7% 112.1% 151.6% 212.5% 266.3% 75-79 100.0% 156.3% 177.4% 193.8% 236.9% 325.3% 466.5% 80-84 100.0% 150.4% 203.1% 229.1% 245.7% 297.5% 402.6% 85+ 100.0% 130.6% 176.9% 235.1% 286.9% 324.6% 389.4% Total 100.0% 130.4% 158.4% 191.2% 239.7% 306.6% 397.1% GM Project G.6 A - 16 October 2000
Table A.5.1. Projected Total Fatality Rate Attributed to Male Drivers, Deaths per 100 Million Miles National 1995 2000 2005 2010 2015 2020 2025 65-69 1.61 1.68 1.65 1.62 1.58 1.55 1.52 70-74 2.09 2.25 2.17 2.10 2.02 1.95 1.89 75-79 3.43 3.72 3.65 3.58 3.52 3.46 3.40 80-84 9.51 8.05 7.89 7.72 7.58 7.43 7.31 85+ 13.88 14.02 13.03 12.13 11.33 10.60 10.01 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 1.61 1.41 1.38 1.35 1.32 1.29 1.26 70-74 1.86 1.90 1.83 1.75 1.69 1.62 1.57 75-79 3.20 3.14 3.08 3.01 2.95 2.88 2.83 80-84 7.91 7.13 6.95 6.78 6.61 6.44 6.31 85+ 14.24 13.08 12.42 11.79 11.19 10.62 10.19 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 1.15 1.41 1.38 1.35 1.32 1.28 1.26 70-74 2.29 1.89 1.82 1.75 1.68 1.62 1.57 75-79 3.11 3.13 3.07 3.00 2.94 2.87 2.83 80-84 5.33 5.36 5.23 5.10 4.97 4.85 4.75 85+ 13.50 13.05 12.38 11.76 11.16 10.59 10.16 South 1995 2000 2005 2010 2015 2020 2025 65-69 1.76 2.04 2.00 1.95 1.91 1.86 1.83 70-74 2.32 2.75 2.64 2.54 2.44 2.35 2.27 75-79 3.95 4.55 4.45 4.35 4.26 4.17 4.10 80-84 19.88 10.31 10.05 9.80 9.56 9.32 9.13 85+ 19.79 18.92 17.96 17.05 16.18 15.36 14.73 West 1995 2000 2005 2010 2015 2020 2025 65-69 1.69 1.59 1.56 1.52 1.48 1.45 1.42 70-74 1.86 2.14 2.06 1.98 1.90 1.83 1.77 75-79 3.08 3.54 3.46 3.39 3.32 3.25 3.19 80-84 7.08 8.02 7.82 7.63 7.44 7.26 7.11 85+ 7.57 8.15 6.56 5.28 4.25 3.43 2.79 GM Project G.6 A - 17 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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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 194 and 195: Table A.4.2. 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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