Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table A.5.2. Projected Total Fatality Rate Attributed to Male Drivers, Deaths per 100 Million Miles, as Percentage of 1995 Rates National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 104.5% 102.6% 100.6% 98.5% 96.3% 94.7% 70-74 100.0% 107.6% 103.9% 100.3% 96.7% 93.2% 90.3% 75-79 100.0% 108.4% 106.4% 104.5% 102.7% 100.8% 99.3% 80-84 100.0% 84.7% 83.0% 81.2% 79.7% 78.2% 76.9% 85+ 100.0% 101.1% 93.9% 87.4% 81.7% 76.4% 72.1% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 88.1% 86.1% 84.1% 82.2% 80.3% 78.8% 70-74 100.0% 101.9% 97.9% 94.1% 90.5% 87.0% 84.3% 75-79 100.0% 98.1% 96.0% 93.9% 91.9% 90.0% 88.4% 80-84 100.0% 90.1% 87.9% 85.7% 83.5% 81.5% 79.8% 85+ 100.0% 91.9% 87.2% 82.8% 78.6% 74.6% 71.5% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 122.7% 119.9% 117.1% 114.5% 111.8% 109.8% 70-74 100.0% 82.6% 79.4% 76.3% 73.4% 70.5% 68.3% 75-79 100.0% 100.9% 98.8% 96.7% 94.6% 92.6% 91.0% 80-84 100.0% 100.5% 98.0% 95.6% 93.2% 90.9% 89.1% 85+ 100.0% 96.6% 91.7% 87.1% 82.6% 78.4% 75.2% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 116.0% 113.3% 110.7% 108.2% 105.7% 103.7% 70-74 100.0% 118.6% 114.0% 109.6% 105.3% 101.3% 98.1% 75-79 100.0% 115.0% 112.5% 110.1% 107.8% 105.5% 103.6% 80-84 100.0% 51.8% 50.6% 49.3% 48.1% 46.9% 45.9% 85+ 100.0% 95.6% 90.7% 86.1% 81.8% 77.6% 74.4% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 94.2% 92.1% 90.0% 87.9% 85.9% 84.3% 70-74 100.0% 114.8% 110.4% 106.1% 102.0% 98.0% 95.0% 75-79 100.0% 115.0% 112.6% 110.2% 107.8% 105.5% 103.7% 80-84 100.0% 113.3% 110.5% 107.8% 105.1% 102.5% 100.4% 85+ 100.0% 107.7% 86.7% 69.8% 56.2% 45.3% 36.8% GM Project G.6 A - 18 October 2000
Table A.5.3. Projected Total Fatality Rates Attributed to Female Drivers, Deaths per 100 Million Miles National 1995 2000 2005 2010 2015 2020 2025 65-69 1.47 1.65 1.62 1.59 1.56 1.52 1.50 70-74 2.52 2.25 2.18 2.10 2.03 1.95 1.89 75-79 4.34 3.58 3.51 3.46 3.39 3.32 3.27 80-84 6.18 6.59 6.41 6.24 6.07 5.90 5.78 85+ 11.82 11.30 10.68 10.08 9.53 9.00 8.58 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 1.29 1.41 1.38 1.35 1.32 1.29 1.26 70-74 2.23 1.90 1.83 1.75 1.69 1.62 1.57 75-79 5.14 3.14 3.08 3.01 2.95 2.88 2.83 80-84 6.17 7.13 6.95 6.78 6.61 6.44 6.31 85+ 16.08 13.08 12.42 11.79 11.19 10.62 10.19 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 1.30 1.41 1.38 1.35 1.32 1.28 1.26 70-74 2.56 1.89 1.82 1.75 1.68 1.62 1.57 75-79 3.49 3.13 3.07 3.00 2.94 2.87 2.83 80-84 6.06 7.11 6.93 6.76 6.59 6.43 6.30 85+ 24.01 13.05 12.38 11.76 11.16 10.59 10.16 South 1995 2000 2005 2010 2015 2020 2025 65-69 1.80 2.04 2.00 1.95 1.91 1.86 1.83 70-74 2.57 2.75 2.64 2.54 2.44 2.35 2.27 75-79 5.61 4.55 4.45 4.35 4.26 4.17 4.10 80-84 6.80 6.00 5.85 5.70 5.56 5.42 5.31 85+ 10.56 11.01 10.45 9.92 9.42 8.94 8.57 West 1995 2000 2005 2010 2015 2020 2025 65-69 1.26 1.44 1.40 1.37 1.34 1.31 1.29 70-74 2.75 2.14 2.06 1.98 1.90 1.83 1.77 75-79 2.66 2.81 2.75 2.70 2.64 2.58 2.54 80-84 5.33 6.38 6.22 6.07 5.92 5.77 5.66 85+ 7.10 7.21 6.84 6.49 6.16 5.85 5.61 GM Project G.6 A - 19 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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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 200 and 201: Table A.5.4. 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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