摘要
传统停车引导方法受到寻优搜索算法本身缺陷的影响,设计的引导路径无法实现全局最优。针对该点不足设计了一种基于GA-DE-PSO优化算法的停车场车辆高效引导方法。利用栅格法建立停车场环境栅格地图。在原有停车时间最小化目标的基础上,增加一个避碰目标函数,由此建立一个多目标函数模型。将GA与DE融合到一起后利用GA-DE优化PSO算法,通过GA-DE-PSO优化求解停车场车辆最佳引导方案。结果表明与三种传统方法相比,GA-DE-PSO优化算法求出的方案所耗费的停车时间更短、效率更高,能够引导驾驶员快速识别出最近车位。
The traditional parking guidance methods are affected by the inherent defects of the optimization search algorithm,and the designed guidance path often cannot achieve global optimization.In view of the shortcomings of this point,an efficient vehicle guidance method based on GA-DE-PSO optimization algorithm is designed for parking lots.In this study,the grid method is used to establish a grid map of the parking lot environment.On the basis of the original goal of minimizing parking time,a collision avoidance objective function is added to establish a multi-objective function model.After integrating GA and DE,GA-DE is used to optimize the PSO algorithm,and GA-DE-PSO is used to optimize the optimal guidance scheme for parking lot vehicles.The results show that compared with the three traditional methods,the GA-DE-PSO optimization algorithm tekes a shorter parking time,indicating that this method is more efficient and can guide drivers to complete parking behaviors more quickly.
作者
罗小军
黄燧福
王筱珍
Luo Xiaojun;Huang Suifu;Wang Xiaozhen(School of Intelligent Engineering,Guangzhou Nanyang Polytechnic College,Guangzhou,Guangdong 510800,China;School of Electrical Engineering,Guangzhou City University of Technology,Guangzhou,Guangdong 510800,China)
出处
《黑龙江工业学院学报（综合版）》
2024年第2期94-99,共6页
Journal of Heilongjiang University of Technology(Comprehensive Edition)
基金
2020年度广东省普通高校青年创新人才项目(项目编号:2020KQNCX245)。
