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This work regards our preliminary investigation on the problem of pathplanning for autonomous vehicles that move on a freeway. We approach thisproblem by proposing a driving policy based on Reinforcement Learning. Theproposed policy makes minimal or no assumptions about the environment, since noa priori knowledge about the system dynamics is required. We compare theperformance of the proposed policy against an optimal policy derived viaDynamic Programming and against manual driving simulated by SUMO trafficsimulator.

A Deep Reinforcement Learning Driving Policy for Autonomous Road Vehicles