ACCIDENT COST-SAVING AND HIGHWAY ATTRIBUTES

Two semi-logarithmic regression models are developed to estimate accid ent rates and accident costs, respectively, for rural non interstate h ighways in the state of Iowa. Data on 21,224 accidents occurring betwe en 1989 and 1991 on 17,767 road segments are used in the analysis. Sev en road attributes of these road segments are included as predictor va riables. Applying the resulting regression models to a rather typical highway upgrade situation, the present value of the accident cost savi ng is computed. The sensitivity of the estimated cost saving to values for fatal, personal injury, and property damage only accidents is tes ted. Because factors other than road characteristics greatly influence accident costs, the models developed in this research explain a limit ed amount of the variance in these costs among road segments. Results of the analysis indicate that the most important attribute associated with accident costs is average daily traffic per lane, followed by con ditions requiring passing restrictions and the sharpness of curves. Va rying the values for the three categories of accidents shows that resu lts are far more sensitive to the value of personal injuries than fata lities. The feasibility of using predictive models of accident costs i n benefit-cost analyses of highway investments is demonstrated.