Autonomous Racing using Learning Model Predictive Control
  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. 
Ugo Rosolia, Ashwin Carvalho and Francesco Borrelli
cs.LG math.OC