Analysis of Truck-Involved Rear-End Crashes Using Multinomial Logistic Regression

Among truck-involved crash types, rear-end collisions result in the third largest number of fatalities and have the second largest crash frequency. Using two national crash databases (2000-2004), the Fatality Analysis Reporting System (FARS) and the General Estimates System (GES), overall and fatal truck-involved rear-end collisions were both investigated in this paper. Three groups were used to classify two-vehicle rear-end collisions in this study. Using the vehicle's striking/struck role as a basis, the crash categories were: car-car (car hitting car), car-truck (car hitting truck), and truck-car (truck hitting car). There was comparison of occurrence conditions of the three rear-end crash types so that potential risk factors associated with the truck-involved crashes, such as driver characteristics, highway designs, and road environments, could be identified. The multinomial logistic regression results show a significant association between overall truck-involved rear-end crashes and factors such as gender, driver age, alcohol use, speed, day of week, interstate, weather condition, divided/undivided highway, and lighting condition. There was also a significant association between fatal truck-involved rear-end collisions and gender, driver age, alcohol use, day of week, divided/undivided highway, and lighting condition. More information regarding effective crash countermeasures and a better understanding of track-related rear-end crash risk are provided by this study.