Molecular Dynamics-based Modelling of Lane-changing Behaviors of Connected Autonomous Vehicle
YANG Yuxiang1, QU Dayi1, CUI Shanning1, WANG Tao1, WANG Kedong1,2
1. Department of Transportation Engineering, Qingdao University of Technology, Qingdao 266520, China; 2. Intelligent Manufacturing Institute, Qingdao Huanghai University, Qingdao 266520, China
Abstract：Vehicle driving behavior is constrained by multi-dimensional elements of complex traffic scenes, and its lane-changing decision is the key in the field of automatic driving. In order to solve the defect of traditional lane-changing model ignoring inter-vehicle interactions, the relationship between inter-vehicle interactions and inter-molecular forces is analyzed, and based on the molecular interaction Buckingham potential function, a vehicle lane-changing decision-making model is established. Relying on SUMO software, the model is compared and analyzed with SL2015 lane changing model in terms of safety, efficiency and comfort. The results show that the interaction potential decision model reduces the number of dangerous lane changes by 45%; the average speed increases by 3.38% and the average number of passes improves by 5.12%. The interaction potential model systematically describes the inter-vehicle interaction relationship, and provides a theoretical basis for internet-connected autonomous vehicles to make safe, efficient and comfortable lane-changing decisions.
杨宇翔, 曲大义, 崔善柠, 王韬, 王可栋. 基于分子动力学的网联自主车辆换道决策模型[J]. 复杂系统与复杂性科学, 2026, 23(4): 142-151.
YANG Yuxiang, QU Dayi, CUI Shanning, WANG Tao, WANG Kedong. Molecular Dynamics-based Modelling of Lane-changing Behaviors of Connected Autonomous Vehicle[J]. Complex Systems and Complexity Science, 2026, 23(4): 142-151.
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