Developing Truck Corridor Crash Severity Index

Abstract

According to NHTSA, more than 400,000 truck accidents occurred in 2009 and approximately 7,800 of those were fatal crashes. Compared with extensive studies conducted on freeway truck safety, the research on arterial streets is considerably disproportionate. Making the connections between truck traffic generators, arterial streets are key links in door-to-door deliveries. There is an urgent need to study truck safety on arterial streets because of the strong growth of truck traffic. Truck-related crashes are expected to be reduced through careful planning of the location, design, and operation of driveways, median openings, street connections, and street sections. Through the collection of extensive data on selected arterial corridors that are heavily used by trucks, contributing factors to truck crash frequency and severity were identified with a negative binomial model and multinomial logit model. Corridor truck miles traveled, annual average daily traffic, signal density, shoulder width, and pavement serviceability index and its standard deviation are significant factors for crash frequency prediction. The multinomial logit model identified 12 causal factors for crash severity, such as posted speed limit, lane width, number of lanes, pavement condition index, and undivided roadway portion. Subsequently, a crash severity index for truck arterial corridors was developed. The findings from the study not only will benefit state and local agencies in planning, design, and management of a safer truck arterial corridor, but will also help carriers to optimize their routes from a safety perspective.