Adaptive optimal control of connected vehicles

In this paper, a data-driven non-model-based approach is proposed for the adaptive optimal control of connected vehicles, comprised of n human-driven vehicles only transmitting motional data and an autonomous vehicle in the tail receiving the broadcasted data from preceding vehicles by wireless vehicle-to-vehicle (V2V) communication devices. An optimal control problem is formulated to minimize the errors of distance and velocity and to optimize the fuel usage. By employing adaptive dynamic programming (ADP) technique, optimal controllers are obtained by online approximation for the connected vehicles without knowing the system dynamics. The effectiveness of the proposed approach is demonstrated via online learning control of the connected vehicles in two scenarios.