Model-free Deep Reinforcement Learning for Urban Autonomous Driving

Urban autonomous driving decision making is challenging due to complex road geometry and multi-agent interactions. Current decision making methods are mostly manually designing the driving policy, which might result in suboptimal solutions and is expensive to develop, generalize and maintain at scal...

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Bibliographic Details

Published in:	2019 IEEE Intelligent Transportation Systems Conference (ITSC) pp. 2765 - 2771
Main Authors:	Chen, Jianyu, Yuan, Bodi, Tomizuka, Masayoshi
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2019
Subjects:	Autonomous vehicles Decision making Learning (artificial intelligence) Machine learning Roads Routing Task analysis
Online Access:	Get full text
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