Development of hazard-specific truck crash modification factors for cold-region rural highways

Abstract

This study attempts to develop (i) truck safety performance functions (SPFs), and (ii) hazard-specific crash modification factors (CMFs), for cold-region rural highways. Police-reported truck-involved crashes on rural highway segments of Alberta, Canada, were used to develop truck SPFs for four crash severity levels: total, fatal, personal injury (PI), and property damage only. Three settings of the Poisson–Tweedie regression modeling approach representing Poisson, geometric Poisson, negative binomial distributions were used to develop truck SPFs; the negative binomial distribution was deemed as the most appropriate distribution to model truck-involved crashes for all crash severity levels. The CMF for poor visibility (CMF = 1.5) suggests that poor visibility increases PI-type truck-involved crashes on rural two-lane two-way highway segments by 50% as compared to the number of such crashes attributed to crash causes other than transportation hazards. Road safety researchers may adopt the methodology to effectively rank hazard risks to highway freight transportation systems.