Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table B.5. Male DRI Income Projections National 1995 2000 2005 2010 2015 2020 2025 65-69 20,020 21,490 22,771 24,245 25,485 26,818 28,127 70-74 17,531 18,210 18,436 18,904 19,929 21,216 22,467 75-79 16,381 17,029 17,770 18,911 20,124 21,229 22,389 80-84 14,716 15,390 16,204 17,382 18,457 19,301 20,181 85+ 12,880 13,335 13,876 14,670 15,436 16,074 16,737 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 20,095 21,945 23,781 25,662 26,812 28,172 29,547 70-74 17,826 18,128 18,209 18,665 19,513 20,575 21,603 75-79 16,512 16,761 17,015 17,473 18,155 18,914 19,711 80-84 15,451 15,687 16,285 17,531 18,317 18,773 19,216 85+ 13,677 14,241 14,913 15,908 16,877 17,689 18,539 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 21,461 23,272 24,821 26,293 27,517 28,702 29,895 70-74 17,808 18,465 18,747 19,102 19,871 20,770 21,652 75-79 16,410 17,515 18,202 18,802 19,707 20,570 21,432 80-84 15,267 15,400 15,852 16,845 17,568 18,080 18,609 85+ 13,628 14,201 14,791 15,589 16,418 17,128 17,864 South 1995 2000 2005 2010 2015 2020 2025 65-69 18,165 19,091 19,853 21,032 22,033 23,186 24,257 70-74 16,194 17,251 17,711 18,258 19,534 21,112 22,671 75-79 15,024 16,032 17,161 18,701 20,212 21,623 23,133 80-84 13,878 15,218 16,460 17,788 19,345 20,709 22,149 85+ 11,783 12,332 12,988 13,980 14,984 15,856 16,778 West 1995 2000 2005 2010 2015 2020 2025 65-69 22,545 24,122 25,321 26,735 28,352 29,945 31,524 70-74 19,337 19,702 19,629 20,084 21,118 22,523 23,840 75-79 18,303 19,000 19,604 20,796 22,372 24,071 25,817 80-84 15,041 15,542 16,173 17,168 18,029 18,680 19,358 85+ 12,781 12,986 12,978 13,237 13,762 14,448 15,081 GM Project G.6 B - 8 October 2000
Table B.6. Female DRI Income Projections National 1995 2000 2005 2010 2015 2020 2025 65-69 9,656 10,313 10,742 11,458 12,273 13,228 14,134 70-74 9,382 9,964 10,285 10,762 11,335 12,110 12,835 75-79 9,738 10,037 10,239 10,674 11,208 11,767 12,295 80-84 9,780 10,452 11,041 11,862 12,665 13,493 14,313 85+ 9,555 10,001 10,419 11,155 11,983 12,791 13,603 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 10,306 10,814 11,083 11,806 12,700 13,736 14,697 70-74 9,884 10,260 10,382 10,738 11,230 11,909 12,518 75-79 10,028 10,021 10,001 10,314 10,682 11,081 11,430 80-84 10,202 10,823 11,263 11,875 12,669 13,464 14,229 85+ 10,250 10,688 10,953 11,435 12,223 13,099 13,966 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 10,164 10,873 11,313 11,868 12,554 13,306 14,023 70-74 9,699 10,255 10,559 11,071 11,614 12,355 13,032 75-79 9,915 10,428 10,820 11,321 11,798 12,327 12,833 80-84 9,997 10,536 10,832 11,164 11,684 12,224 12,744 85+ 9,830 10,222 10,671 11,532 12,250 12,799 13,327 South 1995 2000 2005 2010 2015 2020 2025 65-69 8,763 9,188 9,428 9,997 10,732 11,576 12,371 70-74 8,709 9,469 9,921 10,438 11,113 12,004 12,865 75-79 8,856 9,165 9,436 10,037 10,713 11,367 11,991 80-84 8,937 9,502 10,091 11,045 11,988 12,811 13,640 85+ 8,618 9,294 9,967 10,886 11,833 12,630 13,451 West 1995 2000 2005 2010 2015 2020 2025 65-69 10,195 11,339 12,225 13,312 14,263 15,478 16,647 70-74 10,243 10,706 10,952 11,371 11,788 12,396 12,943 75-79 10,700 11,121 11,275 11,508 12,044 12,658 13,252 80-84 10,706 11,395 11,628 12,062 12,998 14,179 15,337 85+ 12,781 12,557 12,291 12,495 12,831 13,312 13,729 GM Project G.6 B - 9 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
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10. SUMMARY, CONCLUSIONS, AND RECOM
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similarly relied on a regression mo
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trend of fatal crashes in the futur
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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
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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 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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