重庆理工大学学报(自然科学) ›› 2023, Vol. 37 ›› Issue (4): 50-56.

• 车辆工程 • 上一篇    下一篇

改进麻雀搜索算法的智能车路径规划研究

陈佳峻,范 英,代晓文   

  1. 太原科技大学 交通与物流学院,太原 03002
  • 出版日期:2023-05-06 发布日期:2023-05-06
  • 作者简介:陈佳峻,男,硕士研究生,主要从事车辆路径规划方面的研究,Email:chenjiajun34355671@163.com;通信作者 范 英,男,硕士,副教授,主要从事载运工具方面研究,Email:fanying2751@163.com。

Research on intelligent vehicle path planning based on an improved sparrow search algorithm

  • Online:2023-05-06 Published:2023-05-06

摘要: 针对麻雀搜索算法存在的收敛速度慢和容易陷入局部最优等缺点,提出了一种改 进的麻雀搜索算法。首先,使用 ICMIC混沌映射函数初始化种群,提高种群多样性,以此来增强 麻雀种群在未知环境的探索能力。其次,对麻雀算法位置更新公式进行修改,对位置更新公式 进行优化,提高算法的收敛速度。最后,设计 3个不同的栅格地图,将改进后的麻雀搜索算法与 原始算法在此地图中进行路径规划对比,验证改进麻雀搜索算法的性能。实验结果表明:改进 后的麻雀搜索算法在智能车路径规划问题中有着更好的表现,具有更快的收敛速度和更好的寻 优能力。

关键词: 车辆工程, 路径规划, 改进麻雀搜索算法, 混沌映射

Abstract: Aiming at the shortcomings of the sparrow search algorithm such as slow convergence speed and easy falling into local optimum, this paper proposes an improved sparrow search algorithm. Firstly, the ICMIC chaotic mapping function is used to initialize the population and improve the diversity of the population so as to enhance the ability of the sparrow population to explore in unknown environments. Secondly, the position update formula of the sparrow algorithm is modified and optimized to improve its convergence speed. Finally, three different grid maps are designed, and the improved sparrow search algorithm and the original algorithm are compared in this map for path planning to verify the performance of the improved sparrow search algorithm. The experimental results show that the improved sparrow search algorithm has better performance in intelligent vehicle path planning, with faster convergence speed and better optimization ability.

中图分类号: 

  • U495