交通运输系统工程与信息

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (3): 214-225.DOI: 10.16097/j.cnki.1009-6744.2026.03.020

• 智能交通系统与信息技术 • 上一篇    下一篇

混合交通流场景下基于改进人工势场法的队列协同换道控制

徐晓美* ，符蒙，赵峻伟，张涌   

  1. 南京林业大学，汽车与交通工程学院，南京210037
  • 收稿日期:2026-02-09 修回日期:2026-03-15 接受日期:2026-03-19 出版日期:2026-06-25 发布日期:2026-06-23
  • 作者简介:徐晓美（1977— ），女，江苏泰兴人，教授，博士。
  • 基金资助:
    江苏省产业前瞻与关键核心技术项目 (BE2022053-2)。

Cooperative Lane-change Control for Vehicular Platoons Based on Improved Artificial Potential Field Method in Mixed Traffic Flow

XU Xiaomei*, FU Meng, ZHAO Junwei, ZHANG Yong   

  1. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
  • Received:2026-02-09 Revised:2026-03-15 Accepted:2026-03-19 Online:2026-06-25 Published:2026-06-23
  • Supported by:
    Jiangsu Province's Industry Outlook and Key Core Technology Projects (BE2022053-2)。

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摘要： 面向混合交通流场景下汽车队列的换道问题，本文开展基于改进人工势场法的队列协同换道控制研究。首先，提出队列换道双层决策模型，一次决策感知环境是否安全，二次决策针对周围车辆类型选择适合当前场景的换道策略；其次，通过人工势场法实现队列换道动作，针对传统方法忽略车辆运动学约束的问题，引入Dubins曲线规划路径，构建适应网联环境的多势场模型，生成满足车辆运动学约束的平滑换道轨迹，保证所规划路径的物理可执行性；最后，搭建换道场景，仿真验证队列协同换道控制的可行性和有效性。研究表明，引入Dubins曲线的改进方法能规划出光滑的换道路径；所提协同换道方法能实现队列动态避障，相较于非协同换道，协同换道能使后车与队列间的速度误差收敛至0m·s-1左右，使换道时间缩短38.7%，最小跟车距离缩短15.2%。可见，本文提出的协同换道方法不仅能满足车辆队列的换道安全要求，还提高了交通流运行效率。

关键词: 智能交通, 协同换道, 改进人工势场法, 汽车队列, 混合交通流, Dubins曲线

Abstract: This paper conducts a study on cooperative lane-changing control for vehicular platoons based on an improved artificial potential field method for the lane-changing problem of platoon in mixed traffic flow scenarios. First, a two-layer decision-making model for platoon lane-changing is proposed. The first-layer decision evaluates the safety of surrounding environment, and the second-layer decision selects a lane-changing strategy which is suitable for the current scenario based on the surrounding vehicle types. Subsequently, the platoon lane-changing maneuver is realized with an artificial potential field (APF) method. To address the limitation of traditional methods which ignore the vehicle kinematic constraints, a Dubins curve-based path planning method is introduced to construct a multi-potential-field model that adapts to the networked environment. While the smooth lane-changing trajectories that meet vehicle kinematic constraints are generated to ensure the physical feasibility of the planned path. Finally, a lane-changing scenario is constructed and the feasibility and effectiveness of the collaborative lane-changing control method for the platoon are verified through simulation. The results show that the proposed method incorporating Dubins curves can plan smooth lane-changing paths; the proposed collaborative lane-changing method can achieve dynamic obstacle avoidance for the platoon; compared to the non-cooperative lane-changing, the cooperative lane-changing strategy can reduce the speed error between the following vehicle and the platoon to approximately 0 m·s-1, shorten the lane-changing time by 38.7%, and reduce the minimum following distance by 15.2%. The proposed cooperative lane-changing method not only satisfies the safety requirements of vehicular platoons during lane-changing, but also improves the operational efficiency of traffic flow.

Key words: intelligent transportation, cooperative lane-change, improved artificial potential field method, vehicular platoons, mixed traffic flow, Dubins curves

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