卡车
运输工程
危害
环境科学
撞车
工程类
法律工程学
土木工程
计算机科学
汽车工程
化学
有机化学
程序设计语言
作者
Rillagoda G.N. Yasanthi,Babak Mehran,Phani Kumar Patnala,Jonathan D. Regehr,Chaouki Regoui
标识
DOI:10.1139/cjce-2023-0436
摘要
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.
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