Abstract

This investigation focused on characterizing commercial vehicle safety in rural Montana on the basis of driver, vehicle, cargo, carrier, operating environment and crash characteristics using advanced statistical modeling methods. Montana, like other rural states experiences unique challenges in regards to commercial vehicle safety. Crashes typically involve a single vehicle, occur at higher speeds, are more severe and take longer to be detected. In order to address these challenges, researchers utilized statistical modeling to characterize commercial vehicle safety levels on the basis of the various characteristics. Model interpretation was intended to assist public agencies in focusing scarce regulatory and enforcement resources on commercial vehicles highest at-risk for safety-related problems. The agencies would then be able to perform their duties more effectively and efficiently by addressing safety problems in a preventative rather than reactionary manner. An ordered probit model was used to model the 6524 crashes that took place over a seven-year period. The results of this investigation were directly interpretable in regards to magnitude and direction. Independent variables that were found to have a significant influence on the severity of a crash included driver characteristics (age, condition-normal, condition-asleep, driver state residence), vehicle characteristics (vehicle configuration-single unit 2-axle), cargo characteristics (household goods), carrier characteristics (carrier physical address-Canadian Territories, number of trip leased and intrastate drivers, latest review-compliance review), operating environment characteristics (crash years