WiseMove: A Framework to Investigate Safe Deep Reinforcement Learning for Autonomous Driving
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WiseMove is a platform to investigate safe deep reinforcement learning (DRL) in the context of motion planning for autonomous driving. It adopts a modular architecture that mirrors our autonomous vehicle software stack and can interleave learned and programmed components. Our initial investigation focuses on a state-of-the-art DRL approach from the literature, to quantify its safety and scalability in simulation, and thus evaluate its potential use on our vehicle.
This work is supported by the Japanese Science and Technology agency (JST) ERATO project JPMJER1603: HASUO Metamathematics for Systems Design, and by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant: Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles.
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