Research on Path Planning Based on Fusion of Yen’s Algorithm and Ant Colony Algorithm

When solving the K-shortest path (KSP) problem, the most widely used algorithm is Yen’s algorithm. However, Yen’s algorithm only takes the length of the road section as a measurement standard, it does not consider the actual situation of the road section, and the path length difference in the alternative path set is slight. To further obtain a more reasonable path set, this paper will combine the ant colony algorithm by adding the two factors of road travel time and the number of intersections passed. In the experimental results, the differences in the optimal set paths of the two algorithms are compared, and the number of vehicles that choose the recommended path in this paper has a significant advantage in the historical trajectories of vehicles, which proves the effectiveness and rationality of the algorithm.