Application of Improved Astar Algorithm in Global Path Planning of Unmanned Vehicles

Abstract

Path planning is a key part of ensuring that smart vehicles are safe and fast to reach their destination. Currently, global path planning mainly uses Astar algorithm for search planning. Astar algorithm is a heuristic search algorithm, which has been widely used in path planning, but it has many disadvantages, such as: low search efficiency, poor real-time performance, and there are no constraints in search. In view of the shortcomings of Astar algorithm, this paper presents Bidirectional search-Binary tree Astar algorithm(BB-Astar), BB-Astar algorithm has following improvements: First, binary tree data structure is added to the open table of Astar algorithm to optimize the efficiency of the algorithm; Second, use bidirectional search strategy to further improve the efficiency of the algorithm; Thirdly, two kinds of constraint conditions, which must pass through a certain node and a certain road section, are set in the algorithm to make the algorithm more practical. Simulation results show that the search efficiency of the BB-Astar algorithm is better than classic Astar algorithm, and the search with constraints can be completed.