Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

More documents

Recommendations

Info

empirically derived regression coefficients, and similarly with the rate of growth of VMT for each age group over the period 2000 to 2025. The income, health status, other driver, and employment status variables, and the year trend were projected identically to their projections for the proportion of elderly that drives. The year trend variable was a simple count, beginning with 1977 = 1 and increasing by one in each subsequent year. We present the projections of VMT in several formats. We offer a graphical presentation of aggregate national projections of VMT per capita, by age and gender, in Figure 7.3. The numbers underlying the graphs are contained in the tables of Appendix A, Tables A.1.1 through A.1.4, which present Census region as well as national projections. In a pattern of tabular presentations that will carry through each of our projections, the first pair of tables presents projections for males, the second for females. In each pair of tables by gender, the first (Tables A.1.1 and A.1.3 for VMT) presents the actual mileage projections and the second (Tables A.1.2 and A.1.4 for VMT) presents those projections as percents of 1995 actual levels. The national average VMT for the groups of elderly men are projected to rise by 27%-51% over their 1995 levels. VMT in the 65-69 group is projected to experience the largest increase, rising from around 12,400 miles per year in 1995 to a projected 18,800 by 2025. The oldest age group of men, those 85+, experience the smallest increase, from around 5,100 miles in 1995 to 6,500 in 2025. The 2025 VMT projection drops off rather sharply as we move to the 70-74 group of males, with a projected 13,700 miles in that year, while the 75-79 group is close behind with 12,700 projected miles. The drop-off is sharp again as we move to the 80-84 group, with some 8,600 projected miles in 2025. Table A.1.2 presents these mileages as percents of 1995 actual mileage. The elderly women begin from a much smaller base of VMT in 1995, but have greater relative projected increases than men in each age group. The 65-69 women are projected to GM Project G.6 7 - 12 October 2000
each a national average of nearly 11,300 miles, 93% above their 1995 average. The 85+ group is projected to increase its VMT by nearly 78% over 1995 levels, to over 4,900 miles per person in 2025. The smallest increase for any age group is 70% over the 1995 level, among the 75-79 group. These increases put the women’s groups’ VMT by 2025 at levels approximating the VMT of the corresponding groups of men in 1995. The regional patterns of increase are generally not uniform. That is, a percent increase higher than the national average in the VMT of one age group does not necessarily imply that VMT of all age groups in that region will grow more rapidly than the national average. Having offered that rule of thumb, however, VMT growth for all age groups of men in the West and women in the Midwest is lower than the national average, and not simply because their starting (1995) levels were all higher than the national average. 6 Projected VMT growth for the youngest group of elderly men, the 65-69 year olds, is greatest in the Midwest and least in the South, although the differences of 53% over 1995 levels in the Midwest contrasted with only 48.3% in the South are not terribly great. The oldest men’s VMT is projected to grow the most in the South (32.8% over 1995 levels) and the least in the West (23.6%). Among women, the greatest projected VMT growth for 65-69 women occurs in the West (96.0% over 1995) and the lowest in the Northeast and South (88.5% and 89.6%). Among the oldest women, the 85+, the greatest growth occurs in the South (77.0%) and the lowest in the West (64.9%). 6 Only in the South were 1995 VMT levels higher than the national average for each male age group; no region had 1995 VMT uniformly lower than the national average. Among the elderly women, no region had either higher- or lower-than-national-average VMT in 1995 in all age groups. GM Project G.6 7 - 13 October 2000
Page 1:
ORNL-6963 Projecting Fatalities in
Page 4 and 5:
4. ANALYSIS OF DATA SETS ..........
Page 6 and 7:
GM Project G.6 vi October 2000
Page 8 and 9:
LIST OF TABLES Table ES-1 Elderly D
Page 10 and 11:
Table A.5.3 Projected Total Fatalit
Page 12 and 13:
NASS National Automotive Sampling S
Page 14 and 15:
Over the past century, the numbers
Page 16 and 17:
Figure ES-1. Projected Active Drive
Page 18 and 19:
Table ES-1. Elderly Driver Fatality
Page 20 and 21:
1. INTRODUCTION America is graying.
Page 22 and 23:
of existing data bases, including h
Page 24 and 25:
various data sources and their abil
Page 26 and 27:
Finally, data sets should contain,
Page 28 and 29:
• Examine data sources to determi
Page 30 and 31:
health care, resulting in longer li
Page 32 and 33:
Age group Table 3.2. Projected Rati
Page 34 and 35:
that individuals will not retire at
Page 36 and 37:
analysis. Distribution of the elder
Page 38 and 39:
More elderly people live in rural a
Page 40 and 41:
assessments of health status) does
Page 42 and 43:
3.2.2 Impacts of Increasing Frailty
Page 44 and 45:
current vision screening tests at d
Page 46 and 47:
Number of Licenses (thousands) 100
Page 48 and 49:
3.3.2 Changes in Driving Habits In
Page 50 and 51:
Transportation Survey (NPTS) data,
Page 52 and 53:
tourist services, and “smart” s
Page 54 and 55:
Specific highway enhancements to re
Page 56 and 57:
3.4.2 Other GM Project Results (Pro
Page 58 and 59: • As age increased, being struck
Page 60 and 61: men using mid-1990s data, this gend
Page 62 and 63: major contributing factor as was dr
Page 64 and 65: Total (percent) 100 80 60 40 20 0 A
Page 66 and 67: cohort behavior and conditions for
Page 68 and 69: 4.2.3 Drivers and Driving Distance
Page 70 and 71: The HRS and the AHEAD studies are c
Page 72 and 73: these data and weights. Because of
Page 74 and 75: U.S. Census Bureau (http://www.cens
Page 76 and 77: 5. OVERVIEW OF THE MODELING SYSTEM
Page 78 and 79: or acquisition costs, of the goods
Page 80 and 81: institutionalized settings, our pro
Page 82 and 83: elationships between health and the
Page 84 and 85: 6. THE PROPORTION OF THE ELDERLY PO
Page 86 and 87: Employment status represents a deri
Page 88 and 89: statistical relationship exists bet
Page 90 and 91: more likely to be drivers if there
Page 92 and 93: Statistics (BLS) projections beyond
Page 94 and 95: considerably greater proportional c
Page 96 and 97: Table 6.3 (continued) Western Men W
Page 98 and 99: Daily Person Trips/Person Figure 7.
Page 100 and 101: Second, VMT as a consumption item i
Page 102 and 103: century on which we are unable to o
Page 104 and 105: The health status effects are posit
Page 106 and 107: significant one in the final set of
Page 110 and 111: GM Project G.6 7 - 14 October 2000
Page 112 and 113: Table 7.3. Determinants of Projecte
Page 114 and 115: 8. FATAL CRASH RATES 8.1 MODELING F
Page 116 and 117: The other fatality risk concept we
Page 118 and 119: dropped. Since these measures have
Page 120 and 121: have a regular pattern over the age
Page 122 and 123: Table 8.2. Total Risk Crash Rate Re
Page 124 and 125: projection the asymptotic behavior
Page 130 and 131: percentages of people driving, and
Page 132 and 133: 9.1.1 Computations The projection o
Page 134 and 135: Figure 9.2, the combination of thes
Page 136 and 137: Table 9.1. Sensitivity of Total Dri
Page 138 and 139: material, dampening effect on drive
Page 140 and 141: Table 9.2. Sensitivity of 2025 Proj
Page 142 and 143: Age group Table 9.6. Sensitivity of
Page 144 and 145: 9.3.1 The Effect of Time on VMT Pro
Page 146 and 147: Figure 9.4. Projected VMT, Women (U
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 196 and 197:
Table A.4.4. Projected Elderly Driv
Page 198 and 199:
Table A.5.2. Projected Total Fatali
Page 200 and 201:
Page 202 and 203:
Page 204 and 205:
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
show all

Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?