Combined Fast Control of Drifting State and Trajectory Tracking for Autonomous Vehicles Based on MPC Controller

Slipping may cause a vehicle out of control with serious accident potential. However, a kind of car slipping named “drifting” can be seen in professional contests. So, it is reasonable to apply drift maneuvers in autonomous driving. This article proposes a controller for the particular driving skill—drifting based on MPC(Model Predictive Control). Firstly, we analyze drift cornering mechanisms of the 3-state vehicle model and linearize the model at a drifting equilibrium point to build a fast controller. Then, the predicted lateral errors are brought into the MPC cost function to realize trajectory tracking. The algorithm makes use of the expert strategy in car drifting to adjust the steering angle and longitudinal drive force according to lateral errors during the trajectory following. Finally, it is experimentally verified that the proposed controller can track the reference trajectory in real time while maintaining the drifting state.