Driving Tasks Transfer in Deep Reinforcement Learning for Decision making of Autonomous Vehicles

Knowledge transfer is a promising concept to achieve real-time decision-making for autonomous vehicles . This paper constructs a transfer deep reinforcement learning framework to transform the driving tasks in inter-section environments… The driving missions at the un-signalized intersection are cast into a left turn, right turn, and running straight for automated vehicles . The goal of the autonomous ego vehicle (AEV) is to drive through the intersection situation efficiently and safely . This objective promotes the studied vehicle to increase its speed and avoid crashing other vehicles . Simulation results reveal that the decision- making strategies related to similar tasks are transferable . It indicates that the presented control framework could reduce the time consumption .

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Keywords : vehicles - transfer - tasks - driving - decision -

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