Predicting Truck At-Fault Crashes Using Crash and Traffic OffenceData

Introduction:The number of truck-related injuries and deaths can be reduced by understanding the factors that contribute to the higher risk oftruck-related crashes and violations. Truck drivers are at fault of more than 80% of all the truck crashes on Wyoming interstates, andthe literature review indicated that in order to identify appropriate countermeasure to crashes, each crash type should be analyzedindividually. The literature review also revealed that relationships exist between driving records and driver culpability in crashes. Method:This study employed two approaches to identify contributory factors to truck-at-fault fatal and injury crashes, and truck-relatedviolations. Interstate 80, a Wyoming corridor in a mountainous area with one of the highest truck crash rates in the US, was selectedas a case study. Only truck-at-fault crashes and specific types of truck-related violations were considered in this study. The analysesinclude two approaches. First, the logistic regression model was employed to explore vehicle, driver, crash, and environmentalcharacteristics that contribute to truck-at-fault fatal and injury crashes. Second, truck violations were used as a proxy for truckcrashes to examine the tendency to violate truck-related traffic laws in relation to driver and temporal characteristics. Based on theliterature, only violations associated with higher risk of severe crashes were included in the analyses. The included violationsaccounted for more than 70% of all the violations. Result:This study considered more than 30 variables and found that only 10 variables impact truck-at-fault crashes. These factors included:gender, history of past violation, crashes involving multiple vehicles, exceeding the speed limit, occupant distraction, driver ejection,fatigued driving, non-seat belt usage, overturn, and head-on collision. Results of the second analysis indicated that both residencyand time of crash are factors that impact truck-related violations.Results of the analysis also indicated that both residency and timeof the crash are factors that impact truck-related violations