Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Table B.3. Projections of Non-Institutionalized Population, Females National 1995 2000 2005 2010 2015 2020 2025 65-69 5,344,097 5,010,527 5,294,830 6,355,453 8,033,834 9,116,045 10,118,177 70-74 4,923,057 4,791,438 4,503,108 4,778,034 5,750,525 7,266,802 8,244,250 75-79 3,729,854 4,076,868 3,999,011 3,774,837 3,992,599 4,825,222 6,133,231 80-84 2,687,951 2,881,112 3,181,331 3,138,449 2,974,548 3,205,144 3,908,321 85+ 1,891,563 2,177,180 2,447,383 2,799,038 3,046,026 3,115,712 3,377,327 Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 1,252,514 1,162,441 1,200,971 1,382,440 1,711,458 1,924,397 2,093,097 70-74 1,155,573 1,114,784 1,034,305 1,071,645 1,238,990 1,535,905 1,727,367 75-79 916,789 962,469 933,584 868,345 897,110 1,043,791 1,303,033 80-84 674,177 711,001 753,217 733,183 684,077 720,737 848,060 85+ 498,451 563,620 622,489 689,861 734,829 737,855 783,229 Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 1,156,581 992,345 985,908 1,153,851 1,412,038 1,548,197 1,697,843 70-74 1,078,263 1,006,914 868,044 868,628 1,020,925 1,250,850 1,373,495 75-79 836,561 871,303 821,674 714,104 714,236 844,256 1,042,459 80-84 602,810 627,999 662,512 630,496 551,495 563,629 673,489 85+ 432,180 473,561 514,691 568,095 598,692 582,087 601,852 South 1995 2000 2005 2010 2015 2020 2025 65-69 1,911,242 1,878,407 2,034,389 2,484,278 3,170,489 3,622,381 4,063,329 70-74 1,740,774 1,744,729 1,710,211 1,853,628 2,265,411 2,885,942 3,291,998 75-79 1,285,533 1,458,063 1,466,785 1,437,565 1,549,785 1,898,966 2,429,883 80-84 924,682 1,006,997 1,149,336 1,157,652 1,135,747 1,244,460 1,535,827 85+ 629,182 746,923 852,200 992,681 1,094,896 1,140,960 1,255,198 West 1995 2000 2005 2010 2015 2020 2025 65-69 1,023,759 977,334 1,073,562 1,334,884 1,739,850 2,021,071 2,263,908 70-74 948,447 925,011 890,547 984,133 1,225,199 1,594,105 1,851,390 75-79 690,971 785,033 776,968 754,824 831,468 1,038,209 1,357,856 80-84 486,282 535,115 616,266 617,118 603,228 676,319 850,947 85+ 331,750 393,076 458,002 548,401 617,610 654,811 737,049 GM Project G.6 B - 4 October 2000
Table B.4. Projections of Non-Institutionalized Population, Females, as Percent of 1995 Population National 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 93.8% 99.1% 118.9% 150.3% 170.6% 189.3% 70-74 100.0% 97.3% 91.5% 97.1% 116.8% 147.6% 167.5% 75-79 100.0% 109.3% 107.2% 101.2% 107.0% 129.4% 164.4% 80-84 100.0% 107.2% 118.4% 116.8% 110.7% 119.2% 145.4% 85+ 100.0% 115.1% 129.4% 148.0% 161.0% 164.7% 178.5% Midwest 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 92.8% 95.9% 110.4% 136.6% 153.6% 167.1% 70-74 100.0% 96.5% 89.5% 92.7% 107.2% 132.9% 149.5% 75-79 100.0% 105.0% 101.8% 94.7% 97.9% 113.9% 142.1% 80-84 100.0% 105.5% 111.7% 108.8% 101.5% 106.9% 125.8% 85+ 100.0% 113.1% 124.9% 138.4% 147.4% 148.0% 157.1% Northeast 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 85.8% 85.2% 99.8% 122.1% 133.9% 146.8% 70-74 100.0% 93.4% 80.5% 80.6% 94.7% 116.0% 127.4% 75-79 100.0% 104.2% 98.2% 85.4% 85.4% 100.9% 124.6% 80-84 100.0% 104.2% 109.9% 104.6% 91.5% 93.5% 111.7% 85+ 100.0% 109.6% 119.1% 131.4% 138.5% 134.7% 139.3% South 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 98.3% 106.4% 130.0% 165.9% 189.5% 212.6% 70-74 100.0% 100.2% 98.2% 106.5% 130.1% 165.8% 189.1% 75-79 100.0% 113.4% 114.1% 111.8% 120.6% 147.7% 189.0% 80-84 100.0% 108.9% 124.3% 125.2% 122.8% 134.6% 166.1% 85+ 100.0% 118.7% 135.4% 157.8% 174.0% 181.3% 199.5% West 1995 2000 2005 2010 2015 2020 2025 65-69 100.0% 95.5% 104.9% 130.4% 169.9% 197.4% 221.1% 70-74 100.0% 97.5% 93.9% 103.8% 129.2% 168.1% 195.2% 75-79 100.0% 113.6% 112.4% 109.2% 120.3% 150.3% 196.5% 80-84 100.0% 110.0% 126.7% 126.9% 124.0% 139.1% 175.0% 85+ 100.0% 118.5% 138.1% 165.3% 186.2% 197.4% 222.2% GM Project G.6 B - 5 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
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 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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