关键词: 自动驾驶, 速度规划, 模糊规划模型, 神经网络

Abstract: In order to improve the comfort performance of autonomous driving and reduce the time complexity of velocity planning algorithm, a longitudinal velocity planning method based on fuzzy neural network is proposed. Manual driving experience is summarized up as a fuzzy rule table, and a fuzzy planning model is established. By utilizing the self-learning function of neural network, the fuzzy planning model is modified, so as to build the fuzzy neural network planning model. Static obstacle scene and dynamic obstacle scene are analyzed. Simulations verify the algorithm feasibility. Compared with the traditional fuzzy planning method, the proposal have smoother acceleration curve. The proposed method has certain anti-disturbance ability, is easy to implement, and ensures the real-time performance and stability.

Key words: autonomous driving, velocity planning, fuzzy planning model, neural network