Traffic Risk Assessment of Lane-Changing Process in Urban Inter-Tunnel Weaving Segment

Abstract

This study aims to assess the traffic risk of the lane-changing (LC) process in the urban inter-tunnel weaving (UIW) segment. Time to collision (TTC) and extended time to collision (ETTC) are selected as indices for traffic risk assessment. An instantaneous traffic risk level classification method integrating Pareto’s law and the K-means clustering algorithm is proposed. Based on the classification results, the study also proposes an overall LC risk assessment method. Field-collected trajectory data are used to evaluate and characterize the traffic risk associated with the LC process. The instantaneous traffic risk analysis shows that the high-risk state accounts for a high percentage of the LC process in the UIW segment, and the front vehicle on the starting lane has the highest potential for conflict with the target vehicle. The overall risk index analysis shows that the risk distribution of the LC process is significantly clustered in the weaving segment and that the safety level of the UIW segment needs to be improved. This study quantifies the safety level and analyzes the characteristics of traffic risks of the LC process in the UIW segment to provide a decision basis for the development of assisted driving schemes and improvement of traffic safety management in the UIW segment.