吉林大学学报(信息科学版) ›› 2024, Vol. 42 ›› Issue (5): 808-816.

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基于改进JPS 算法的无人车路径规划 

何精武,李伟东   

  1. 大连理工大学汽车工程学院,辽宁大连116024
  • 收稿日期:2023-08-03 出版日期:2024-10-21 发布日期:2024-10-21
  • 作者简介:何精武(1999— ), 男, 长沙人,大连理工大学硕士研究生,主要从事车辆规划控制研究,(Tel)86 -13332222046(E -mail) 624858717@ qq. com; 李伟东(1975— ), 男, 吉林省吉林市人, 大连理工大学副教授, 博士, 硕士生导师, 主要从事车辆 智能化研究,(Tel)86 -15542532298(E -mail)liweidong@ dlut. edu. cn。
  • 基金资助:
    辽宁省科技创新重大专项基金资助项目(ZX20220560) 

Unmanned Vehicle Path Planning Based on Improved JPS Algorithm 

HE Jingwu, LI Weidong    

  1. School of Automobile Engineering, Dalian University of Technology, Dalian 116024, China
  • Received:2023-08-03 Online:2024-10-21 Published:2024-10-21

摘要: 为解决传统JPS(Jump Point Search)算法的拐点多和路径次优等问题, 提出一种改进的跳点搜索算法。 首先, 根据地图可行率,对障碍物进行适应性膨胀,以保障安全距离;其次,结合方向性因素对启发函数进行 调整, 显著提高了路径搜索的目的性;最后,提出了一种能剔除冗余节点的关键点提取策略,优化了初始规划 后的路径, 在保证路径最短的同时,显著减少了拓展节点和拐角。 实验结果表明,与传统的JPS算法相比, 所提算法能缩短路径长度并减少拐角数量,同时拓展节点数量平均减少19%,搜索速度平均提升21.8%。 

关键词: 跳点搜索算法, 障碍物膨胀, 方向性, 关键点提取 

Abstract: To address issues such as excessive turning points and suboptimal paths in traditional JPS(Jump Point Search) algorithms, an improved jump point search algorithm is proposed. First, based on the feasibility of the map, the obstacles are adaptively expanded to ensure a safe distance. Then, an improved heuristic function based on directional factor is integrated. And a key point extraction strategy is proposed to optimize the initial planned path, significantly reducing the number of expanded nodes and turning points while ensuring the shortest path. The experimental results show that compared to traditional JPS algorithms, the proposed ensures a shorter path length and fewer corners, while reducing the number of extended nodes by an average of 19% and improving search speed by an average of 21. 8%. 

Key words:  jump point search algorithm, obstacles expansion, directionality, key node extraction 

中图分类号: 

  • TP242