This paper first explores the relationship between safety and congestion and then examines the relationship between safety and the number of lanes on urban freeways. The relationship between safety and congestion on urban freeways was explored with the use of safety performance functions (SPFs) calibrated for multilane freeways in Colorado, California, and Texas. The focus of most SPF modeling efforts to date has been on the statistical technique and the underlying probability distribution, with only limited consideration given to the nature of the phenomenon itself. In this study neural networks have been used to identify the underlying relationship between safety and exposure.
The modeling process was informed by the consideration of the traffic operations parameters described by the Highway Capacity Manual. The shape of the SPF is best described by a sigmoid reflecting a dose-response type of relationship between safety and traffic demand on urban freeways. Relating safety to the degree of congestion suggests that safety deteriorates with the degradation in the quality of service expressed through the level of service. Practitioners generally believe that additional capacity afforded by additional lanes is associated with more safety. How much safety and for what time period are generally not considered. Comparison of SPFs of multilane freeways suggests that adding lanes may initially result in a temporary safety improvement that disappears as congestion increases. As annual average daily traffic increases, the slope of SPF, described by its first derivative, becomes steeper, reflecting that accidents are increasing at a faster rate than would be expected from a freeway with fewer lanes.