Projecting Fatalities in Crashes Involving Older Drivers, 2000-2025

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Figure 9.6. Component Contributions to Driver Fatality Projections Using Lower-bounded VMT, Women 9.4 USER INTERFACE FOR “WHAT-IF” ANALYSIS The tool for performing “what-if” analysis on the elder driver projections is an Excel 97/2000 spreadsheet. A copy of the spreadsheet can be obtained on the internet via the older drivers link at http://www-cta.ornl.gov or by contacting Tim Reuscher at (865) 574-8690. This spreadsheet utilizes Visual Basic macros, which guide the user through decisions to alter the levels of independent variables used in driver, VMT, and risk projections. The main sheet that the user sees upon opening the spreadsheet is presented below. GM Project G.6 9 - 18 October 2000
Clicking on the “ORNL Projections” link will give the user the option to view the projections presented in the Appendices of this report, displayed by projection type, region, or age group. The “Customized Projections Wizard,” discussed in more detail later, will let the user perform the “what-if” analysis previously described. The “Project Overview” and “Spreadsheet Help” links provide the user with background information on the project and basic help in using the older drivers spreadsheet. 9.4.1 Customized Projections Wizard The “Customized Projections Wizard” is a simple, step-by-step procedure for altering the levels of independent variables (income, “other driver,” employment status, urban population percentages, health status, and seatbelt usage levels) used in projecting the percentage of the population that drives, how much the elderly drive, and their fatality risk per mile driven. Step 1 is a simple introduction to the process. Step 2 requires the user to name the new file which will be created as a result of the wizard, and allows the user to define how the output will be presented. GM Project G.6 9 - 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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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
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Page 136 and 137: Table 9.1. Sensitivity of Total Dri
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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 150 and 151: Step 1: Introduction Step 2: Decisi
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Page 156 and 157: 10. SUMMARY, CONCLUSIONS, AND RECOM
Page 158 and 159: similarly relied on a regression mo
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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
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Table A.5.2. Projected Total Fatali
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Table B.1. Projections of Non-Insti
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Table B.3. Projections of Non-Insti
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B.2. INDEPENDENT VARIABLES PROJECTI
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Table B.5. Male DRI Income Projecti
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B.2.1.2. Projection Adjustments to
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B.2.5 Seatbelt Use Our projections
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C.3. DECREASING GROWTH RATES OF DRI
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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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