Multilevel structural equation modelling reveals causal chains affecting rear-end and side-impact crash risks related to roadway geometry and dynamic traffic flow.
Rear-end and side-impact crash risks are the two principal types of multi-vehicle crash risk on freeways. Most previous studies examine a single crash risk type, limiting understanding of their combined effects. This study employs a multilevel structural equation modelling (SEM) framework to investigate the sequential and joint impacts of roadway geometry, dynamic traffic flow, and driving behaviour on multi-type crash risks. The framework was calibrated using 1,762 rear-end and 1,243 lane-changing conflicts from 14 directional sites. The multilevel SEM accounts for site-level heterogeneity to produce more robust estimates. The path analysis identifies two dominant causal chains: 'Horizontal Curve - Density - Car-following Behaviour - Crash Risk' and 'Vertical Slope - Speed Distribution - Lane-changing Behaviour - Crash Risk'. Low-speed fluctuating traffic flow shows higher crash risks than high-speed stable traffic flow. Car-following behaviour increases both rear-end and side-impact risks, while lane-changing activity raises side-impact risk but reduces rear-end risk.
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Hu et al. (2025) studied this question.
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