Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

More documents

Recommendations

Info

4. ANALYSIS OF DATA SETS ...................................... 4-1 4.1 INTRODUCTION .......................................... 4-1 4.2 ASSESSMENT OF DATA SOURCES .......................... 4-2 4.2.1 Population Data and Projections .......................... 4-2 4.2.2 Income Data ......................................... 4-2 4.2.3 Drivers and Driving Distance Information ................... 4-4 4.2.4 Physical/Functional Limitations ........................... 4-5 4.2.5 Crashes, Casualties, and Fatalities ......................... 4-7 4.2.6 Other Data Categories Considered ........................ 4-9 4.3 CONCLUSIONS ........................................... 4-9 5. OVERVIEW OF THE MODELING SYSTEM ........................ 5-1 5.1 INTRODUCTION TO MODELING ............................ 5-1 5.2 BRIEF EXPLANATION OF DEMAND THEORY ................. 5-2 5.3 POPULATION PROJECTIONS ............................... 5-3 5.4 HEALTH STATUS DATA ................................... 5-6 5.5 ASSUMPTIONS ........................................... 5-8 6. THE PROPORTION OF THE ELDERLY POPULATION THAT DRIVES .. 6-1 6.1 HISTORICAL TRENDS IN ELDERLY DRIVING ................. 6-1 6.2 MODELING THE DECISION TO DRIVE ....................... 6-2 6.3 PROJECTING THE PROPORTION OF OLDER POPULATIONS THAT WILL DRIVE ........................................ 6-7 7. VEHICLE MILES TRAVELED .................................... 7-1 7.1 HISTORICAL TRENDS IN ELDERLY DRIVING ................. 7-1 7.2 EMPIRICAL MODELING OF VMT ............................ 7-3 7.3 PROJECTING VMT ........................................ 7-9 8. FATAL CRASH RATES ......................................... 8-1 8.1 MODELING FATALITY RATES FOR OLDER DRIVERS .......... 8-1 8.2 FATAL CRASH RATE PROJECTIONS ........................ 8-10 8.3 DRIVER FATALITY PROJECTIONS ......................... 8-16 9. ANALYSIS OF THE FATALITY PROJECTIONS ..................... 9-1 9.1 CONTRIBUTIONS OF INDIVIDUAL COMPONENTS TO DRIVER FATALITY PROJECTIONS .................................. 9-1 9.1.1 Computations ........................................ 9-2 9.1.2 Contributions to Driver Fatalities ......................... 9-3 9.2 SENSITIVITY ANALYSIS ................................... 9-4 9.2.1 Total Impacts on Older Driver Fatalities .................... 9-7 9.2.2 Sensitivity of the Projection Components to Individual Variables . 9-9 GM Project G.6 iv October 2000
9.3 A LOWER BOUND FOR DRIVER FATALITIES AND VMT ........ 9-9 9.3.1 The Effect of Time on VMT Projections ................... 9-14 9.3.2 Driver Fatalities with Lower Bounded VMT ................ 9-16 9.4 USER INTERFACE FOR “WHAT-IF” ANALYSIS ............... 9-18 9.4.1 Customized Projections Wizard ......................... 9-19 10. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS .......... 10-1 10.1 SUMMARY OF FINDINGS ................................. 10-1 10.1.1 Aggregate Fatality Projections .......................... 10-1 10.1.2 Comparison of ORNL Aggregate Fatality Projections to Other Studies ............................................ 10-2 10.1.3 Disaggregated Projection Results ........................ 10-8 10.2 CONCLUSIONS ......................................... 10-10 10.3 DIRECTIONS FOR FUTURE RESEARCH .................... 10-12 10.3.1 The Role of Infrastructure and Equipment ................ 10-12 10.3.2 Asymptotic Projection of VMT ......................... 10-12 10.3.3 Additional and Improved Measures of Health Status ......... 10-13 10.3.4 Comparison of Younger and Older Drivers’ Behavior ........ 10-14 10.3.5 Alternate Transportation Options for the Elderly ............ 10-14 REFERENCES ..................................................... R-1 GLOSSARY ....................................................... G-1 APPENDIX A. Endogenous Variable Projections ........................... A-1 APPENDIX B. Exogenous Variable Projections ............................ B-1 APPENDIX C. Notes ................................................ C-1 GM Project G.6 v October 2000
Page 1: ORNL-6963 Projecting Fatalities in
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 108 and 109:
empirically derived regression coef
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 126 and 127:
Page 128 and 129:
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?