融合改进 A*算法与动态窗口法的无人车路径规划研究

doi:10.16638/j.cnki.1671-7988.2025.004.004

汽车实用技术 ›› 2025, Vol. 50 ›› Issue (4): 20-26.DOI: 10.16638/j.cnki.1671-7988.2025.004.004

• 智能网联汽车 • 上一篇

融合改进 A*算法与动态窗口法的无人车路径规划研究

何洋，余孝楠*

辽宁工业大学汽车与交通工程学院

发布日期:2025-02-25
通讯作者: 余孝楠
作者简介:何洋（1982－），男，博士，副教授，研究方向为智能驾驶技术，E-mail:heyang121000@163.com 通信作者：余孝楠（1997－），男，硕士研究生，研究方向为智能驾驶技术，E-mail:yuxiansen97@163.com
基金资助:
2024 年辽宁省教育厅高等学校基本科研项目（LJ212410154021）

Research on Path Planning of Unmanned Vehicles by Integrating Improved A * Algorithm and Dynamic Window Approach

HE Yang, YU Xiaonan*

College of Automobile and Traffic Engineering, Liaoning University of Technology

Published:2025-02-25
Contact: YU Xiaonan

摘要/Abstract

摘要： 针对传统 A *算法在无人车路径规划中搜索效率低、冗余节点及避障灵活性差等问题，提出一种融合改进 A *与动态窗口法的无人车路径规划方法。仿真结果表明，对比传统 A *算法，改进 A *算法在搜索时间平均减少了 66.81%，转折次数平均减少了 43.65%，遍历节点数平均减少了 46.73%，路径长度平均减少了 2.55%，融合算法能在全局最优路径的基础上，达到随机避障效果。

关键词: 无人车；路径规划；A *算法；动态窗口法

Abstract: Aiming at the issues like low search efficiency, redundant nodes and poor obstacle avoidance flexibility of the traditional A* algorithm in the path planning of unmanned vehicles, a method of integrating improved A* and dynamic window approach for unmanned vehicle path planning is proposed. The simulation results show that compared with the traditional A* algorithm, the improved A* algorithm reduces the average search time by 66.81%, the average turn times by 43.65%, the average number of traversing nodes by 46.73%, and the average path length by 2.55%. The fusion algorithm can achieve random obstacle avoidance based on the global optimal path.

Key words: unmanned vehicle; path planning; A* algorithm; dynamic window approach

何洋，余孝楠*. 融合改进 A*算法与动态窗口法的无人车路径规划研究[J]. 汽车实用技术, 2025, 50(4): 20-26.

HE Yang, YU Xiaonan*. Research on Path Planning of Unmanned Vehicles by Integrating Improved A * Algorithm and Dynamic Window Approach[J]. Automobile Applied Technology, 2025, 50(4): 20-26.

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融合改进 A*算法与动态窗口法的无人车路径规划研究

Research on Path Planning of Unmanned Vehicles by Integrating Improved A * Algorithm and Dynamic Window Approach

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