基于分子动力学的网联自主车辆换道决策模型

杨宇翔; 曲大义; 崔善柠; 王韬; 王可栋

doi:10.13306/j.1672-3813.2026.04.017

复杂系统与复杂性科学 >

2026 , Vol. 23 >Issue 4: 142 - 151

DOI: https://doi.org/10.13306/j.1672-3813.2026.04.017

研究前沿

基于分子动力学的网联自主车辆换道决策模型

杨宇翔 ,
曲大义 ,
崔善柠 ,
王韬 ,
王可栋

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1.青岛理工大学交通运输工程系,山东青岛 266520;
2.青岛黄海学院智能制造学院,山东青岛 266520

杨宇翔(2001-),男,山东青岛人,硕士研究生,主要研究方向为智能交通系统分析与决策控制。

网络出版日期: 2026-09-15

基金资助

国家自然科学基金(52272311)

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Molecular Dynamics-based Modelling of Lane-changing Behaviors of Connected Autonomous Vehicle

YANG Yuxiang ,
QU Dayi ,
CUI Shanning ,
WANG Tao ,
WANG Kedong

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1. Department of Transportation Engineering, Qingdao University of Technology, Qingdao 266520, China;
2. Intelligent Manufacturing Institute, Qingdao Huanghai University, Qingdao 266520, China

Online published: 2026-09-15

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摘要

车辆驾驶行为受复杂交通场景多维要素约束,其换道决策是自动驾驶领域的关键。为了解决传统换道模型忽略车辆间相互作用的缺陷,分析了车辆间相互作用与分子间力的关系,基于分子相互作用Buckingham势函数,建立了车辆换道决策模型。依托SUMO软件,从安全性、高效性、舒适性3个方面,与SL2015换道模型对比分析。结果表明,相互作用势决策模型降低了45%的危险换道次数;平均速度提高了3.38%,平均通过数提升了5.12%。相互作用势模型系统描述了车辆间相互作用关系,为网联自主车辆做出安全高效舒适的换道决策提供理论基础。

关键词： 网联自主车辆; 换道决策模型; Buckingham势函数; SUMO仿真

本文引用格式

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 . DOI: 10.13306/j.1672-3813.2026.04.017

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.

Key words： connected autonomous vehicles; lane-change decision modeling; Buckingham potential function; SUMO simulation

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