A*算法在智能车辆路径规划中的应用

Q4 Engineering
Ruili Wang, Zhizhan Lu, Yunfeng Jin, Chao Liang
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引用次数: 1

摘要

路径规划是智能汽车研究领域的重要方向之一。传统的路径规划算法通常使用Dijkstra算法、广度优先搜索(BFS)算法和A*算法。Dijkstra算法是一种基于搜索的算法,可以搜索到最优路径,但缺点是扩展节点太多,导致搜索效率不足。BFS算法是一种启发式搜索算法,它通过启发式函数减少了扩展节点过多的缺点,提高了搜索效率。A*算法是Dijkstra算法和BFS算法相结合的启发式搜索算法,具有更高的搜索效率,可以同时搜索到最优路径,但在搜索模式和规划路径的平滑性方面仍然存在不足。本文首先介绍了一般的路径规划算法,然后介绍和分析了A*算法,并针对其不足提出了改进措施;最后,通过仿真验证了改进算法的可执行性和有效性,并与传统的A*算法进行了比较,结果表明,改进的A*方法对智能车辆的路径规划具有良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of A* algorithm in intelligent vehicle path planning
Path planning is one of the important directions in the field of intelligent vehicles research. Traditional path planning algorithms generally use Dijkstra algorithm, Breadth-First-Search (BFS) algorithm and A* algorithm. Dijkstra algorithm is a search-based algorithm, which can search to an optimal path, but the disadvantage is too many expansion nodes, which leads to insufficient search efficiency. BFS algorithm is a heuristic search algorithm, which reduces the disadvantage of too many expansion nodes and improves the search efficiency by heuristic function. A* algorithm is a heuristic search algorithm that combines Dijkstra's algorithm and BFS algorithm, which has higher search efficiency and can search to an optimal path at the same time, but it is still lacking in the search mode and smoothness of the planned route. This paper first introduces the general path planning algorithm, then introduces and analyzes the A* algorithm, and proposes improvement measures for its shortcomings; finally, the executability and effectiveness of the improved algorithm are tested using simulation, and compared with the traditional A* algorithm, and the results show that the improved A* algorithm has good effect on path planning of intelligent vehicles.
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来源期刊
CiteScore
0.10
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0.00%
发文量
8
审稿时长
10 weeks
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