基于双向蚁群算法的智能小车路径规划方法OA

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.