Developing Safety Performance Function for Freeways by considering Interactions between Speed Limit and Geometric Variables

Safety performance functions (SPFs) are crash prediction models that quantitatively relate the expected number of crash counts with traffic volume and roadway and roadside geometries. SPFs help traffic safety officials identify unsafe locations and take appropriate counteractive measures. A study assembled crash and roadway geometry data of freeways (only Interstate highway data were used for this study) in Connecticut for development of SPFs. Models were estimated separately for single-vehicle and multivehicle crashes. Total and fatal and injury crashes were considered for model estimation for both single-vehicle and multivehicle crashes. For each crash category, three model estimations were performed with negative binomial distribution models with all geometric variables, with speed limit only, and with interaction between speed limit and roadway geometric variables. The best models were selected for each crash category through a comparison of goodness-of-fit measures (Akaike information criterion). Interaction models were found to be the best models for all crash categories. This finding suggests the importance of incorporating the interaction effect between variables, in particular between speed limit and geometric variables such as number of lanes, shoulder width, and median type, for estimation of crash prediction models.