Exploring the Factors Affecting the Injury Severity of Crashes on Mountainous Freeways with High Proportions of Heavy Vehicles Considering Their Heterogeneous and Interactive Effects

Freeway transportation safety issues have attracted public concern in China for decades. This study aims to identify the factors influencing the injury severity of freeway crashes and to quantify their effects on the likelihood of various crash severity levels, with consideration of heterogeneity and interactions. The empirical analysis is based on three years of crash data from two mountainous freeways in Guangdong, China, covering the years of 2021 to 2023. A random parameters logit model with interaction terms is developed for the analysis. Goodness-of-fit indicators reveal that accommodating the interactive effects can significantly improve model fit performance. The estimation results of the parameters and marginal effects indicate that the factors related to vehicle type, time of day, crash season and cause, 3D curvature, and traffic volume have significant effects on crash severity. Notably, interactive effects are revealed between spring and evening, autumn and fixed objects, and non-local vehicles and improper driving. According to the findings, some countermeasures on safety education, traffic management, and freeway design are provided for preventing freeway crash injury, which is helpful for the development of sustainable transportation systems.