Indicators of injury severity of truck crashes using random parameter logit modeling

Crashes involving trucks were more severe and often results in fatal injury crashes. There is an innumerable number of explanatory factors that play an essential role for the accidents involving freight vehicles to happen like roadway design, weather conditions, and driver perception. The Torkham border highway acts as a lifeline for trade between Pakistan and Afghanistan; therefore, its safety analysis is essential. The objective of this study was to perform an extensive study to identify the risk factors that contribute to the injury severity of freight vehicle crashes using explanatory variables. A total of 2500 observations of road traffic crashes were obtained from May 2001 to August 2021 from the accidents recording agencies. Methodologically, a random parameter logit model with heterogeneity in mean and variances was employed to estimate the risk factor using three severity categories namely minor, major, and fatal injuries. 17 explanatory variables show a significant institution with the injury severity of freight vehicles on the Torkham road. Among the identified factors, it was revealed that the probability of the fatal injury severity increases with the increased exposure to freight vehicles; driver-related factors, temporal and environmental characteristics, they were found significant. The significance of this study is to account for the heterogeneity in mean and variances to observe the factors in real-time. Based on the findings, the authors recommend road safety strategies for the mitigation of truck crashes that could proliferate the safe environment for the truck drivers. © 2021 IEEE.