Hierarchical Reinforcement Learning for Dynamic Autonomous Vehicle Navigation at Intelligent Intersections-Reference-Cited by-同舟云学术

Hierarchical Reinforcement Learning for Dynamic Autonomous Vehicle Navigation at Intelligent Intersections

Published:2023-08-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Sun Qian¹^ORCID,Zhang Le²^ORCID,Yu Huan³^ORCID,Zhang Weijia⁴^ORCID,Mei Yu⁵^ORCID,Xiong Hui³^ORCID

Affiliation:

1. The Hong Kong University of Science and Technology, Hong Kong SAR, China

2. Baidu Research, Beijing, China

3. The Hong Kong University of Science and Technology(Guangzhou) & The Hong Kong University of Science and Technology, Guangzhou, China

4. The Hong Kong University of Science and Technology(Guangzhou), Guangzhou, China

5. Baidu Inc., Beijing, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599839

Reference38 articles.

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2. Andrew G Barto and Sridhar Mahadevan . 2003. Recent advances in hierarchical reinforcement learning. Discrete event dynamic systems , Vol. 13 , 1--2 ( 2003 ), 41--77. Andrew G Barto and Sridhar Mahadevan. 2003. Recent advances in hierarchical reinforcement learning. Discrete event dynamic systems , Vol. 13, 1--2 (2003), 41--77.

3. Liyi Chen , Zhi Li , Weidong He , Gong Cheng , Tong Xu , Nicholas Jing Yuan, and Enhong Chen . 2022 . Entity summarization via exploiting description complementarity and salience. IEEE Transactions on Neural Networks and Learning Systems ( 2022). Liyi Chen, Zhi Li, Weidong He, Gong Cheng, Tong Xu, Nicholas Jing Yuan, and Enhong Chen. 2022. Entity summarization via exploiting description complementarity and salience. IEEE Transactions on Neural Networks and Learning Systems (2022).

4. Seung-Bae Cools , Carlos Gershenson , and Bart D'Hooghe . [n.,d.]. Self-Organizing Traffic Lights: A Realistic Simulation . Springer London , London , 45--55. https://doi.org/10.1007/978--1--4471--5113--5_3 10.1007/978--1--4471--5113--5_3 Seung-Bae Cools, Carlos Gershenson, and Bart D'Hooghe. [n.,d.]. Self-Organizing Traffic Lights: A Realistic Simulation. Springer London, London, 45--55. https://doi.org/10.1007/978--1--4471--5113--5_3

5. Xuan Di and Rongye Shi . 2021. A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning. Transportation research part C: emerging technologies , Vol. 125 ( 2021 ), 103008. Xuan Di and Rongye Shi. 2021. A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning. Transportation research part C: emerging technologies , Vol. 125 (2021), 103008.

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