Research on Self-driving Vehicle Path Tracking Adaptive Method Based on Predictive Control

Abstract

The autonomous vehicles can improve the traffic utilisation and ensure the safe driving. Thus, the relative analysis is one hot research topic nowadays. The path tracking control system is one key link for the quick and stable tracking of target paths of autonomous vehicles. For analyzing the route tracing process of the Self-driving vehicles under complex working conditions, this paper proposes an adaptive model prediction controller. The controller chooses a vehicle dynamics model and incorporates a fuzzy adaptive control method into the model predictive control algorithm. Through the fuzzy adaptive control method, the weight of the objective function in the model predictive control algorithm is adaptively optimized to improve the control effects. The joint simulation tests are applied in the CarSim, MATLAB and Simulink software. Compared with the general model predictive controller, the outcomes indicate that the conceptualized controller can effectively reduce the tracking errors and ensure safe driving.