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基于改进混合A*与融合平滑策略的无人车路径规划

刘永涛 赵哲宇 王淞 纳林奇 王泰琪 白凤鹏 宋贵云

汽车工程学报2026,Vol.16Issue(5):779-791,13.
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汽车工程学报2026,Vol.16Issue(5):779-791,13.DOI:10.3969/j.issn.2095‒1469.2026.05.06

基于改进混合A*与融合平滑策略的无人车路径规划

Unmanned Vehicle Path Planning Based on Improved Hybrid A*and Integrated Path Smoothing

刘永涛 1赵哲宇 1王淞 2纳林奇 1王泰琪 1白凤鹏 3宋贵云4

作者信息

  • 1. 长安大学 汽车学院,西安 710064
  • 2. 武警警官学院 信息通信系,成都 610213
  • 3. 抚顺市交通运输综合行政执法队,辽宁,抚顺 113009
  • 4. 新疆美克化工股份有限公司,新疆,库尔勒 841000
  • 折叠

摘要

Abstract

To address the low search efficiency and insufficient path smoothness of unmanned vehicles in complex environments,a path planning method combining an improved Hybrid A* algorithm with an integrated smoothing strategy is proposed.First,a hierarchical ternary node expansion strategy is developed,in which the search direction and steering angle are dynamically adjusted by evaluating the quality of initially expanded nodes,thereby improving the search and optimization capability in complex environments.Second,an integrated smoothing strategy combining the Douglas-Peucker algorithm and B-spline curves is proposed.This strategy removes redundant feature points from the path and fits the remaining key points to generate a smooth path with continuous curvature that satisfies vehicle kinematic constraints.Simulation results show that,in complex obstacle environments,the improved node expansion strategy reduces the computation time by 19.61%and the path length by 13.11%.Compared with B-spline smoothing,the proposed integrated smoothing strategy reduces the average curvature by 28.57%and the cumulative curvature variation by 68.76%.Compared with an improved RRT algorithm,the proposed algorithm reduces the number of expanded nodes by approximately 43.72%in dense-obstacle maps,effectively improving both path planning efficiency and path smoothness for unmanned vehicles.In addition,experiments on a ROS-based Ackermann-steering vehicle platform verify the planning capability of the proposed algorithm in a real physical environment,and the generated paths exhibit better geometric continuity and kinematic feasibility.

关键词

路径规划/混合A*算法/B样条曲线/Douglas-Peucker算法

Key words

path planning/hybrid A* algorithm/B-spline curve/Douglas-Peucker algorithm

分类

交通工程

引用本文复制引用

刘永涛,赵哲宇,王淞,纳林奇,王泰琪,白凤鹏,宋贵云..基于改进混合A*与融合平滑策略的无人车路径规划[J].汽车工程学报,2026,16(5):779-791,13.

基金项目

教育部基础学科和交叉学科突破计划项目(JYB2025XDXM104) (JYB2025XDXM104)

咸阳市重大科技创新专项(L2025-ZDKJ-ZDGG-RGZN-003) (L2025-ZDKJ-ZDGG-RGZN-003)

咸阳市渭城区科技发展计划项目(2025VCCN-03) (2025VCCN-03)

西安市自然科学基金项目(2025JH-ZRKX-0617) (2025JH-ZRKX-0617)

汽车工程学报

2095-1469

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