Application of reliability models for crash frequency analysis: implications for network-wide safety performance

Abstract

The present study demonstrated the potential applications of reliability models for crash analysis of a large highway network. Specifically, three major outcomes of reliability models were investigated: temporal distributions of crashes, reliability score, and expected number of crashes, using 20-year data (2001–2020) of crashes recorded on the Saskatchewan highway network. A series of reliability models were developed for crashes by crash severity, vehicle involvement, and highway type. First, the temporal distributions of crashes on each segment were fit to a statistical distribution. Second, the reliability scores were used to rank the high crash risk segments. Third, the mean expected crash frequency was used to develop network-wide safety performance functions for total and fatal crashes in urban and rural highway segments using Poisson–Tweedie (PTw) regression models. The developed PTw models showed that the presence of trucks in the traffic composition has a significant effect on crash frequency, especially for urban highway segments.