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This study aims to explore the variability of risk factors affecting injury severity in rear-end crashes when different struck vehicle groups are involved. Two types of rear-end crash data, vehicle-strike-car data, vehicle-strike-truck data, are extracted from the Fatality Analysis Reporting System (FARS). Two likelihood ratio (LR) tests are firstly performed to validate the struck vehicle group variations, and then two separate random thresholds random parameters hierarchical ordered probit (RRHOP) models (Model 1 and Model 2) are established to capture unobserved heterogeneity. The results of LR test show significant differences in the effects of factors included in each model. Moreover, the model results suggest that SUVs, vans, and large trucks as striking vehicles are significant related to injury severity in both models with different effects. Factors such as speeding related, pickup, model year (struck vehicle), disabled damage, adverse weather, speed limit (≥60 mile/h), and young driver (struck vehicle) are found to be statistically significant in only model 1. These results provide a better understanding of differences in contributing factors of rear-end crashes, which help to propose effective countermeasures to mitigate its injury severity.

journal of transportation safety and security

Analysis of factors affecting occupant injury severity in rear-end crashes by different struck vehicle groups: A random thresholds random parameters hierarchical ordered probit model