Model Predictive Stabilization Control of High speed Autonomous Ground Vehicles

This paper presents a model predictive control (MPC) scheme for the stabilization of high-speed autonomous ground vehicles (AGVs) considering the effect of road topography. Accounting for the road curvature and bank angle, a single-track dynamic model with roll dynamics is derived. Variable time-steps are utilized for vehicle model discretization, enabling collision avoidance in the long-term without compromising the prediction accuracy in the near-term. Accordingly, safe driving constraints such as sideslip envelope, zero-moment-point, and lateral safety corridor are developed for the handling stability and obstacle avoidance. Taking these constraints into account, an MPC problem is formulated and solved at each step to determine the optimal steering control commands. Moreover, feedback corrections are integrated into the MPC to compensate the unmodeled dynamics and parameters uncertainties. Simulations carried out in Matlab/CarSim environment validated the capability and real-time ability of the proposed control scheme.