ME PhD candidate Ashwin Carvalho and former PostDoc Stéphanie Lefévre, along with ME Professor Francesco Borrelli, have won the 2017 IEEE Transactions on Automation Science and Engineering Best Paper Award. The award, given by the IEEE Robotics & Automation Society, recognizes the best paper published in the previous calendar year, and is judged on technical merit, originality, potential impact on the field, clarity of presentation, and practical significance for applications. The award-winning paper from the MPC Lab members, A Learning-Based Framework for Velocity Control in Autonomous Driving, presents a method for personalizing the driving style of an autonomous car, where the driving styles are learned from human drivers. Lefévre says, "The motivation is twofold. Firstly, autonomous cars can benefit from the experience acquired by human drivers over years of driving. Secondly, different drivers have different expectations regarding how an autonomous car should behave. We implemented the proposed approach for autonomous car following and tested it on highways in California. The results showed that our car is able to learn from human drivers and to reproduce their driving style."