Intelligent Identification of Moving Trajectory of Autonomous Vehicle Based on Friction Nano-Generator

The purpose of this paper is to explore an intelligent identification method of autonomous vehicle moving trajectory based on friction nano-generator. This method uses friction nano-generator to obtain energy from the friction between the vehicle tire and the ground, and realizes the perception and recognition of the vehicle motion state. On this basis, through the analysis and processing of the motion state data, an intelligent identification model of the moving trajectory of autonomous vehicles is established to realize the intelligent prediction and control of the driving trajectory of vehicles. Therefore, a large number of vehicle movement state data is collected, and the data are preprocessed and feature extracted, and an intelligent recognition model of vehicle movement trajectory is constructed by machine learning method. Finally, the accuracy and stability of the model are verified by experiments, and the feasibility and practicability of the method are proved. The results show that the intelligent identification method of autonomous vehicle trajectory based on friction nano-generator has high accuracy and practicability. In the field verification environment, the lateral position deviation, heading angle deviation and minimum radius of curvature of the trajectory recognition algorithm for autonomous vehicles are 0.2193m, 10deg and 5.9m, respectively. The lateral deviation of the real vehicle test is kept within 0.5m, and the lateral acceleration is infinitely close to zero. This autonomous path identification is extremely stable. This method can not only realize intelligent prediction and control of vehicle trajectory, but also provide data support for self-learning and optimization of autonomous vehicles.