Abstract

Truck crashes in Wyoming are considered a major issue. Nearly 26% of crashes on rural interstate roads involve hazardous materials (HAZMAT) trucks. Wyoming has a high rate of activities related to the energy industry, as it is considered among the top energy producing states in the U.S.A., and mainly relies on the trucking industry for transportation. A crash involving a HAZMAT shipment might have a catastrophic impact because of the nature of the HAZMAT shipment. Therefore, it is crucial to identify the traffic safety performance of HAZMAT trucks, so suitable countermeasures can be identified to reduce the frequency and severity of these crashes. This study aims to develop safety performance functions (SPFs) for crashes involving HAZMAT utilizing traditional negative binomial (NB) models, as well as variations of the NB model, namely, NB-1 and NB-P. The results indicate that HAZMAT truck crashes are associated with vehicle miles traveled, truck percentage, horizontal and vertical characteristics of road geometry, pavement type, and speed limit. The findings from this study show that the NB-P models outperformed the traditional NB models based on likelihood ratio tests, information criteria, and prediction measures. Relevant insights are made on traditional countermeasures, such as road geometry, warning signs, slippery road surface warnings, and climbing lanes, as well as non-traditional countermeasures including updating variable speed limit (VSL) algorithms, adding variable message signs, and integrating roadway geometry information into connected vehicle applications in Wyoming. These could be considered to assist stakeholders and emergency management agencies in better decision making toward safer operations of HAZMAT trucks.

Full Text
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