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Factors and paths influencing multi-type crash risks on freeway curves: multilevel structural equation modelling
Zhenlin Hu1, Bijiang Tian1, Pengru Wei1
1School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin, China.
This study reveals how roadway design, traffic flow, and driver actions jointly influence freeway crash risks. Understanding these combined effects is crucial for improving road safety and preventing accidents.
Area of Science:
- Traffic Safety
- Transportation Engineering
- Accident Analysis
Background:
- Freeway safety is challenged by rear-end and side-impact collisions.
- Previous research often isolates single crash types, limiting comprehensive understanding.
Purpose of the Study:
- To investigate the sequential and joint impacts of roadway geometry, traffic flow, and driving behavior on multiple freeway crash types.
- To develop a robust framework for analyzing complex crash risk factors.
Main Methods:
- Utilized a multilevel structural equation modeling (SEM) framework.
- Calibrated the model with 1,762 rear-end and 1,243 lane-changing conflict datasets from 14 freeway sites.
- Accounted for site-level heterogeneity for enhanced estimation accuracy.
Main Results:
- Identified two primary causal pathways: 'Horizontal Curve - Density - Car-following Behavior - Crash Risk' and 'Vertical Slope - Speed Distribution - Lane-changing Behavior - Crash Risk'.
- Low-speed, fluctuating traffic flow correlates with higher crash risks compared to high-speed, stable flow.
- Car-following behavior elevates both rear-end and side-impact risks; lane-changing behavior increases side-impact risk but decreases rear-end risk.
Conclusions:
- Roadway geometry, traffic dynamics, and driver behavior interact complexly to influence multi-type crash risks.
- Specific geometric features and traffic flow conditions create distinct risk profiles for different crash types.
- Findings provide insights for targeted safety interventions on freeways.
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