End to end autonomous driving simulation based on reinforcement learning

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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Bibliographic Details
Main Author: Wong, Kenzhi Iskandar
Other Authors: Lyu Chen
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Engineering
Online Access:https://hdl.handle.net/10356/177154

Internet

https://hdl.handle.net/10356/177154

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