End to end autonomous driving simulation based on reinforcement learning
This paper presents a comprehensive study that explores the application of reinforcement learning (RL) algorithms, specifically Deep Q-Network (DQN) and Soft Actor Critic (SAC), in the context of end-to-end autonomous driving. The research project utilizes the SMARTS Simulator, an open-source softwa...
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格式: | Final Year Project (FYP) |
语言: | English |
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Nanyang Technological University
2024
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在线阅读: | https://hdl.handle.net/10356/177154 |