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This document summarizes a survey on using deep reinforcement learning techniques for autonomous driving. It begins by introducing autonomous driving as a sequential decision making problem that can be addressed using reinforcement learning. It then provides a taxonomy of autonomous driving tasks that have been approached using deep reinforcement learning, including driving policy, predictive perception, path planning, motion planning, and low-level controller design. The document reviews literature on appl

Author

祁朋

Language

EN