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WAD: A Deep Reinforcement Learning Agent for Urban Autonomous Driving
Urban autonomous driving is an open and challenging problem to solve as the decision-making system has to account for several dynamic factors like multi-agent interactions, diverse scene perceptions, complex road geometries, and other rarely occurring real-world events.
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