Abstract
The development of the automobile industry and the increase in car ownership has brought great traffic pressures to the city, among which, the difficulty of parking has become a serious problem to the majority of drivers. An automatic parking system can help drivers to complete parking operation or automatic parking task, and a decision control system is an important part of automatic parking system. In this paper, a strategy for generating the shortest parking path based on a bidirectional breadth-first search algorithm combined with a modified Bellman–Ford algorithm is proposed for automatic parking systems. Experimental results show that this scheme can improve the performance of an automatic parking system, especially in a complex environment.
Highlights
Before the parking experiment based on the strategy in this paper, the parking environment must the parking experiment based on the strategy in this paper, the parking environment must be collected first, and the grid map must be completed
In this paper, according to the characteristics of the working environment of automatic parking system, combined with different types of parking environment, an automatic parking path planning decision control system based on bidirectional breadth-first search algorithm combined with the modified Bellman–Ford algorithm was designed, which successfully overcomes the shortcomings of the existing traditional methods
The motion model was studied, the motion space constraints were generated, and the parking end conditions were given according to the relative positions of vehicles and parking spaces
Summary
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