  A novel learning Model Predictive Control technique is applied to the
autonomous racing problem. The goal of the controller is to minimize the time
to complete a lap. The proposed control strategy uses the data from previous
laps to improve its performance while satisfying safety requirements. Moreover,
a system identification technique is proposed to estimate the vehicle dynamics.
Simulation results with the high fidelity simulator software CarSim show the
effectiveness of the proposed control scheme.
