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Obstacle Avoidance Path Planning for Intelligent Vehicles Based on Improved RRT Algorithm

Ziyao Zhou,Huifang Kong,Qian Zhang, Chenshun Wang

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)(2023)

School of Electrical Engineer and Automation

Cited 0|Views10
Abstract
Aiming at the problem of time inefficiency caused by blind search of traditional rapid exploring random tree (RRT) algorithm for obstacle avoidance path planning of intelligent vehicles, an improved RRT algorithm is proposed. Firstly, the search area of the RRT algorithm is restricted according to the equations of motion and steering constraints of the vehicle. Then, an artificial potential field (APF) method is introduced to guide the RRT expansion nodes, which accelerates the convergence speed of the algorithm. Finally, the generated path is pruned to make the path planning smoother and shorter. The comparison of the proposed algorithm with the traditional RRT algorithm in the MATLAB platform shows that the proposed algorithm in this paper has superior performance in terms of search nodes, the time required for path planning, and path security performance.
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intelligent vehicles,RRT,APF,path planning,obstacle avoidance
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要点】:本文提出了一种改进的RRT算法,用于智能车辆的避障路径规划,通过限制搜索区域、引入人工势场方法引导节点扩展,以及修剪生成的路径,提高了搜索效率和路径质量。

方法】:通过改进的RRT算法进行路径规划。

实验】:在MATLAB平台上,将提出的算法与传统的RRT算法进行了比较,结果显示提出的算法在搜索节点数量、路径规划所需时间以及路径的安全性方面具有优越性能。