Tire Modeling to Enable Model Predictive Control of Automated Vehicles From Standstill to the Limits of Handling
Model predictive control (MPC) frameworks have been effective in collision avoidance, stabilization, and path tracking for automated vehicles in real-time. These MPC formulations use a variety of vehicle models that capture specific aspects of vehicle handling, focusing either on low-speed scenarios or highly dynamic maneuvers. However, these models individually are unable to handle all operating regions with the same performance. This work introduces a novel linearization of a brush tire model that is affine, timevarying, and effective at any speed. We incorporate this tire model into a convex MPC formulation for lateral control on a low friction surface. Experimental results on an automated Volkswagen Golf GTI demonstrate effective steering control for path tracking from a standstill up to the limits of tire-road friction.
14th International Symposium on Advanced Vehicle Control (AVEC 2018)