Intelligent Fuzzy Obstacle Avoidance System for Autonomous Vehicle Parking

Autonomous vehicle parking has been improved significantly in recent years. There are many methods for achieving this goal, and fuzzy control is one of them. Due to parallel parking’s complexity in the presence of obstacles, an autonomous system can minimize errors and accelerate the process. This study first implements a fuzzy parallel parking system from the literature and then adds a fuzzy obstacle avoidance system. This system uses two fuzzy controllers to reduce the possibility of running into the point and continuous obstacles during parking, where a decision controller switches from one to the other as necessary. Also, some modifications to the surrounding vehicle sensors are done for better reactions. The final system is simulated in challenging environments with static and dynamic obstacles, demonstrating its robustness and superior performance. Considering that autonomous vehicles are gaining attention worldwide, this study can assist in developing automatic intelligent parking systems.