With the advancement in machine learning, access to data with V2X connectivity, and more reliable plant model simulation, reinforcement learning has been considered recently as a control design option for the feedback control of automotive systems. In this talk, the challenges of applying classic control methods with focus on PID structure are briefly discussed and a perspective to deploy reinforcement learning to address some of these challenges is presented.