融合多源势场的公路作业区智能驾驶动态路径规划

doi:10.16097/j.cnki.1009-6744.2026.01.011

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (1): 115-124.DOI: 10.16097/j.cnki.1009-6744.2026.01.011

• 智能交通系统与信息技术 • 上一篇下一篇

融合多源势场的公路作业区智能驾驶动态路径规划

马健霄¹，王雨¹，陆涛^*1，白莹佳¹，王羽尘^1,2，赵顗¹

1. 南京林业大学，汽车与交通工程学院，南京210037；2.东南大学，交通学院，南京211189

收稿日期:2025-10-17 修回日期:2025-11-24 接受日期:2025-12-17 出版日期:2026-02-25 发布日期:2026-02-15
作者简介:马健霄（1966—），男，内蒙古赤峰人，教授，博士。
基金资助:
国家自然科学基金(62303228)；江苏省交通运输科技与成果转化项目(2022Y10)。

Dynamic Path Planning for Intelligent Driving in Road Work Zone Considering Multi-source Potential Fields

MA Jianxiao¹, WANG Yu¹, LU Tao^*1, BAI Yingjia¹, WANG Yuchen^1,2, ZHAO Yi¹

1. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China; 2. School of Transportation, Southeast University, Nanjing 211189, China

Received:2025-10-17 Revised:2025-11-24 Accepted:2025-12-17 Online:2026-02-25 Published:2026-02-15
Supported by:
National Natural Science Foundation of China (62303228)；Jiangsu Transportation Technology and Achievement Transformation Project (2022Y10)。

摘要/Abstract

摘要： 为提高智能驾驶车辆途经公路作业区时的行驶安全性，本文提出一种针对智能驾驶感知特性的动态路径规划算法。首先，针对公路作业区段的道路环境，基于势场理论构建道路边界势场、车道线势场、车辆势场以及公路作业区势场；然后，基于建立的多源势场，通过归一化和权重分配，构建公路作业区路段融合势场，并提出基于时间滑动的动态低势场通道路径规划算法（D-LPC）；最后，通过仿真实验评估路径轨迹、速度曲线、最小作业区距离、加速度曲线、Jerk指标、路径曲率和通行效率等关键指标，并与典型路径规划模型进行对比，验证D-LPC算法在安全性、舒适性及通行效率方面的优越能力。结果显示，车辆在作业区的最大和最小速度分别为118.80km·h^-1和60.12km·h^-1，与作业区的最小距离为2.85m，总通行时间为272s，平均速度61.81 km·h^-1，在保证安全的同时维持了高效的通行效率。研究成果可为智能驾驶车辆在作业区场景下的实时安全动态路径规划策略提供理论和技术支撑，对提升自动驾驶车辆在非结构化环境中的适应能力与自主规划能力具有重要意义。

关键词: 智能交通, 动态路径规划, 风险势场, 公路作业区, 交通安全

Abstract: To improve the safety of intelligent vehicles traveling through highway work zones, this study proposes a dynamic path planning algorithm considering the perception characteristics of intelligent driving. First, based on potential field theory, the potential fields for road boundaries, lane lines, vehicles, and the highway work zone are constructed for the road environment of the highway work zone. Then, based on the established multi-source potential fields, a fused potential field for the highway work zone is constructed through normalization and weight assignment. A dynamic low-potential channel path planning algorithm (D LPC) is proposed based on time sliding. The simulation experiments evaluate key metrics such as path trajectory, speed profile, minimum work zone distance, acceleration profile, Jerk index, path curvature, and traffic efficiency. The results were compared with the typical path planning models, and the performance of the D-LPC algorithm was verified in terms of safety, comfort, and traffic efficiency. The results show that the maximum and minimum vehicle speeds in the work zone are 118.80 km·h^-1 and 60.12 km·h^-1, respectively, with a minimum distance from the work zone of 2.85 meters. The total travel time is 272 seconds, and the average speed is 61.81 km·h^-1, ensuring safety while maintaining high traffic efficiency. The study results provide theoretical and technical support for the real-time safe dynamic path planning strategy of intelligent driving vehicles in work area scenarios, and is helpful to improve the adaptability and autonomous planning capabilities of autonomous driving vehicles in unstructured environments.

Key words: intelligent transportation, dynamic path planning, risk potential field, highway work area, traffic safety

中图分类号:

U491

马健霄, 王雨, 陆涛, 白莹佳, 王羽尘, 赵顗. 融合多源势场的公路作业区智能驾驶动态路径规划[J]. 交通运输系统工程与信息, 2026, 26(1): 115-124.

MA Jianxiao, WANG Yu, LU Tao, BAI Yingjia, WANG Yuchen, ZHAO Yi. Dynamic Path Planning for Intelligent Driving in Road Work Zone Considering Multi-source Potential Fields[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(1): 115-124.

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链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2026.01.011

http://www.tseit.org.cn/CN/Y2026/V26/I1/115

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融合多源势场的公路作业区智能驾驶动态路径规划

Dynamic Path Planning for Intelligent Driving in Road Work Zone Considering Multi-source Potential Fields

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