基于蚁群算法的新能源汽车最优行驶路径规划
Optimal driving path planning for new energy vehicles based on ant colony algorithm
滕卓易1
作者信息
- 1. 广西现代职业技术学院,广西 河池 547000
- 折叠
摘要
为了提高新能源汽车的行驶效率、更有效地利用能源,文章提出了基于蚁群算法的最优行驶路径规划方法.在建立新能源汽车运动学模型后,利用蚁群算法确定新能源汽车的活动路径节点参数,从而构建路径规划目标函数,再通过求解目标函数,得到最优的行驶路径规划结果.实验结果表明,该方法能够有效规划出起点与终点之间的最短路径,缩短新能源汽车的行驶距离,提高行驶效率.
Abstract
In order to improve the driving efficiency of new energy vehicles and make more effective use of energy,this study proposes an optimal driving path planning method based on ant colony algorithm.After establishing the kinematic model of new energy vehicles,this study uses ant colony algorithm to determine the activity path node parameters of new energy vehicles,thereby constructing a path planning objective function.Then,by solving the objective function,the optimal driving path planning result is obtained.The experimental results show that this method can effectively plan the shortest path between the starting and ending points,shorten the driving distance of new energy vehicles,and improve driving efficiency.
关键词
蚁群算法/新能源汽车/行驶路径/路径规划Key words
ant colony/new energy vehicles/driving path/path planning引用本文复制引用
基金项目
广西现代职业技术学院校级立项科研项目(2022)(GXXDYB202230)
出版年
2024
NETL
NSTL
万方数据