Optimization of an Intelligent Controller for Parallel Autonomous Parking

Autonomous parking has become the research focus. Fuzzy controller was ofen used to solve the nonlinear and time-varying problem of the autonomous parking. According to the shortcomings of traditional fuzzy controller, a new ant colony algorithm based on idle ant effect was proposed. Firstly, the fuzzy controller was designed based on the kinematic equations. Then, multi-colony parallel optimization was adopted to improve the data initialization, path construction and pheromone update. The method guaranteed the completeness of the membership function and made the fuzzy parameters with higher precision. Finally, both traditional controller and the designed controller were used for the autonomous parking, the experimental results showed that, comparing with the traditional fuzzy controller, the designed controller can improve the stability problem with less error and faster response speed.