Abstract: A system for controlling a vehicle includes a processor configured to execute instructions stored on a non-transitory computer readable medium. The system also includes a sensor coupled to the processor and configured to receive sensory input. The system also includes a controller coupled to the processor and configured to control the vehicle. The processor is further configured to: create a synthetic image based on the sensory input; derive a deep reinforcement learning (RL) policy using the synthetic image, wherein the deep RL policy determines a longitudinal control for the vehicle; and instruct the controller to control the vehicle based on the deep RL policy.

Abstract: A system for controlling a vehicle includes a first sensor for detecting at least one environment characteristic. The system also includes a driver characteristic input device configured to receive at least one driver characteristic corresponding to a driving style of a driver. The system also includes a controller that includes a reinforcement learning adaptive cruise control that is in communication with the first sensor and the driver characteristic input device, the reinforcement learning adaptive cruise control being configured to: determine a target behavior for the vehicle based on the at least one environment characteristic and the at least one driver characteristic; and selectively control the vehicle based on the target behavior.