RESEARCH ON URBAN ROAD TRAFFIC SAFETY RISK IDENTIFICATION METHOD BASED ON ABNORMAL DRIVING BEHAVIOR
Abstract
To address the issues of ambiguity and subjectivity in current road traffic safety risk identification, this paper proposes a quantitative evaluation method for urban road traffic safety risk based on abnormal driving behavior data. Firstly, abnormal driving behaviors (such as speeding, sudden acceleration, sudden deceleration, sharp lane changes, and sharp turns) are identified on road segments using GPS trajectory data, and an indicator system of abnormal driving behavior rates is constructed. Based on this, the AHP-EW integrated weighting method is employed to determine the weight of each behavior on safety risk. Combined with the fuzzy comprehensive evaluation method, a road traffic safety risk assessment model is established to achieve quantitative risk grading. Validation using actual road segments in a city in Shandong Province demonstrates that this method can effectively identify high-risk road sections, providing traffic management departments with accurate and real-time data support for road network safety risk identification and control.
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