Conflict-Based Safety Performance Functions for Predicting Traffic Collisions by Type

Abstract

In road safety analysis, safety performance functions (SPFs) are used to predict the average number of collisions per year at a road site. SPFs are a function of various amounts of exposure and, in some cases, site-specific characteristics. Exposure is a measure of opportunities for collisions to occur. The circulating traffic volume is commonly adopted for this purpose. However, not all vehicles interact unsafely at a road site. Alternatively, traffic conflicts may provide a more appropriate exposure measure for collisions because they represent only unsafe interactions between vehicles. There has been some research on this topic, mainly based on aggregated data including all conflict types. In this study a stratified analysis was conducted by type of conflict. Hence, the main objectives of this research were to establish a relationship between predicted collisions and predicted conflicts by using an SPF with traffic conflicts as an exposure measure and to predict the number of specific types of conflicts and collisions at signalized intersections. The methodological framework used was a two-phase nested modeling process in which a Poisson–gamma SPF that uses traffic volume as exposure was used to predict conflicts, which were then used in another Poisson–gamma SPF to predict collisions. The proposed approach was applied to a data set of collision frequency and average hourly conflicts for 49 signalized intersections throughout British Columbia, Canada. The results demonstrate the proportional relationship between conflicts and collisions and the importance of carrying out stratified analyses when types of conflicts are combined.