Interpretable analysis of risk factors for intercity bus operation safety on plateau roads using the SHAP method
利用青海省10条城际客车线路两个月GPS轨迹数据，通过随机森林和SHAP方法量化了高原环境、驾驶疲劳和道路类型对客车运行风险的影响，为制定针对性安全措施提供依据。
Identifying and analyzing factors that influence traffic risk is crucial for reducing crash frequency and severity. This is particularly true for intercity buses operating on high-altitude plateaus, where unique environmental and topographical conditions heighten operational risks. However, quantitative research on how these factors influence traffic operation risk in such contexts, especially across freeways, general highways, and urban roads, remains insufficient. This study uses two months of GPS trajectory data from 10 intercity bus routes in Qinghai province, China to address this gap. We assessed traffic operation risks at discrete road segments using three indicators: Coefficient of Speed Variation (CSV), Severity of Rapid Acceleration (SRA), and Severity of Rapid Deceleration (SRD). A Random Forest regression model, interpreted by the SHAP method, was employed to explore the complex effects of influencing factors. The results quantify the unique risks of the plateau environment, showing that driving instability surges at high altitudes, and the impact is significantly amplified by high speeds. The analysis further highlights the operational risks of intercity buses, identifying a clear fatigue threshold where continuous driving leads to more frequent aggressive maneuvers. Critically, the research differentiates these risks by road type, demonstrating a shift in dominant safety factors, as road geometry poses a greater threat on general highways than on freeways. These findings provide quantitative evidence for developing targeted safety interventions that address the unique operational risks of plateau roadways.