佛山大学学报（自然科学版）2026，Vol.44Issue(4)：60-67,8.
基于双向蚁群算法的智能小车路径规划方法
Intelligent car path planning method based on bidirectional ant colony algorithm
摘要
Abstract
To optimize the path planning effect of intelligent vehicles,a method based on bidirectional ant colony algorithm is proposed.An intelligent car path planning environmental map is constructed based on the free space and obstacle grid,using a bidirectional search strategy.Two groups of ant colonies search in parallel from the initial point and the endpoint,and connect nodes into a complete path through the ant encounter mechanism.Heuristic functions and dynamic volatiliy coefficient are set to guide ants towards the target point,and the optimal path is determined based on transition probability and pheromone update mechanism.When the iteration number is reached or the encounter condition is met,the optimal path is output as the the final planning result.The results show that the proposed method can achieve convergence as quickly as possible after application,with a corresponding path distance of 62.0 m and a travel time cost of 84.0 s.关键词
双向蚁群算法/路径规划/栅格地图/双向搜索/启发函数Key words
bidirectional ant colony algorithm/path planning/grid map/bidirectional search/heuristic function分类
信息技术与安全科学引用本文复制引用
李白华..基于双向蚁群算法的智能小车路径规划方法[J].佛山大学学报（自然科学版）,2026,44(4):60-67,8.基金项目
安徽省高等学校省级科研重点项目(2022AH052622) （2022AH052622）
