Velocity Planning Method Base on Fuzzy Neural Network for Autonomous Vehicle

In order to improve the comfort performance and reduce the planning algorithm complexity in autonomous vehicle, an intelligent longitudinal velocity planning method based on fuzzy neural network (FNN) is proposed. With the manual driving experience, fuzzy planning model is established. By utilizing the self-learning function of neural network, fuzzy planning model is modified, which is attempted to establish FNN planning model. The planning method is applied to velocity planning. Three kinds of driving scenes are analyzed, and velocity planning models based on FNN are established accordingly. The simulation and experiment results indicate that acceleration generated by FNN planning model has good smooth property, and it is easy to be tracked by the subsequent control module. Compared with traditional method, the proposed method has certain anti-disturbance ability and self-adaptability. Also, the proposed method is convenient for engineering application, which ensures both the real-time performance and stability of the algorithm.