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Title: SIMPLIFIED APPROACH TO FORECAST HIGHWAY CRASH RATES OF SELECTED SPECIAL POPULATION SUBSETS
Accession Number: 00771211
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: Time series models developed by regression to forecast highway crash rates in association with some selected special population subsets are described here. Such models are useful for assessing the safety performance of the subsets because the problems inherent in subsets are different from those of the average highway population. They also enable high-risk groups to be identified, not only under present conditions but also in the future. Two sets of models were developed: one for the state of Florida and the other for the United States. The population subsets considered included older drivers, young drivers, international tourists, and school-age children as nonmotorists. Among the different model formats tried, the negative exponential was the best fitting and gave reasonably good fitness, as indicated by considerably high R-squared values varying from 0.784 to 0.974. The main purpose of the model building was to forecast the crash rates by each population subset at various time points within the study horizon. Previous studies by other researchers where forecast values were compared with actual values have indicated that most of the complex models were incapable of explaining the future situation. As such, the opinion of the authors is that simple models with year as the independent variable could be advantageous for forecasting the safety performance of the highway system for special population groups.
Supplemental Notes: This paper appears in Transportation Research Record No. 1665, Statistical Methods in Transportation and Safety Data Analysis for Highway Geometry, Design, and Operations.
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Dissanayake, SLu, J JChu, XPagination: p. 44-50
Publication Date: 1999
Serial: ISBN: 0309070651
Features: Figures
(7)
; References
(18)
; Tables
(5)
TRT Terms: Geographic Terms: Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics
Files: TRIS, TRB, ATRI
Created Date: Oct 21 1999 12:00AM
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