运动规划
启发式
平滑度
A*搜索算法
计算机科学
路径(计算)
任意角度路径规划
职位(财务)
算法
数学优化
功能(生物学)
运动学
航向(导航)
人工智能
工程类
数学
机器人
航空航天工程
数学分析
物理
财务
经典力学
进化生物学
经济
生物
程序设计语言
作者
Pengyu Wang,Yanglin Liu,Weimin Yao,Yuanbin Yu
标识
DOI:10.1177/09544070221100677
摘要
Path planning is a fundamental problem in the aspect of autonomous driving. A-star (A*) algorithm is a heuristic algorithm for path planning. However, there are two problems need to be solved in the traditional A-star algorithm: firstly, the tracking error caused by vehicle speed and vehicle size are not considered in path planning; secondly, the kinematics constraints of the vehicle itself and the smoothness of the path in the actual driving process are not considered. Therefore, this paper proposes an improved A-star algorithm to address the above deficiencies. By designing the collision cost heuristic function based on the position of obstacles, the vehicle contour and speed are considered and the vehicle safety is improved by setting a safe space around the vehicle, and establishing a steering cost heuristic function based on the control of heading angle difference, the vehicle dynamics constraints are satisfied, so as to improve the feasibility of path planning. The experimental results show that the improved A-star algorithm can avoid vehicle contours collision at different speeds and output a smoother path, and effectively generate higher quality path.
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