Analysis of design attributes and crashes on the Oregon highway system : final report.
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2001-08-01
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Abstract:This report has investigated the statistical relationship between crash activity and roadway design attributes on the Oregon state
highway system. Crash models were estimated from highway segments distinguished by functional classification (freeway v.
non-freeway) and location (urban v. non-urban). A number of design attributes were found to be statistically related to crash
activity in the various models, including the number of lanes, curve characteristics, vertical grade, surface type, median type,
turning lanes, shoulder width, and lane width. In selected instances, CRFs calculated from crash model results were compared
to those presently used to evaluate projects in ODOT’s Safety Improvement Program.
The range of design attributes addressed in this study is similar to what has been covered by other studies reported in the crash
modeling literature, and the results obtained for Oregon are generally consistent with those obtained from other study areas.
Although relatively few at present, the number of design attributes included in crash models will likely grow over time as
automated roadway inventory data become increasingly available. Nevertheless, it is doubtful that the coverage of crash
models will ever be sufficiently comprehensive to effectively substitute for the present system, which encompasses hundreds of
countermeasures in differing contexts.
While the number of highway design attributes specified in crash models is limited, they represent a relatively large share of the
capital invested in safety improvements. Safety-related outlays for lane and shoulder widening, altering horizontal and vertical
curves, introducing median treatments, and for resurfacing have very large cost implications compared to outlays for signage
and markings. Cross-sectional crash models usually specify variables that represent countermeasures associated with the more
costly outlays. Thus, the models provide states with an opportunity to validate the CRFs that are most important economically.
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