Network-Wide Traffic Signal Control Based on MARL With Hierarchical Nash-Stackelberg Game Model-Reference-Cited by-同舟云学术

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Network-Wide Traffic Signal Control Based on MARL With Hierarchical Nash-Stackelberg Game Model

Published:2023 Issue: Volume:11 Page:145085-145100
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Shen Hui¹,Zhao Hongxia²,Zhang Zundong³^ORCID,Yang Xun³,Song Yutong³,Liu Xiaoming³

Affiliation:

1. School of Electrical and Control Engineering, North China University of Technology, Beijing, China

2. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

3. Beijing Key Laboratory of Urban Road Traffic Intelligent Technology, North China University of Technology, Beijing, China

Funder

National Natural Science Foundation Project

China National Railway Group Company Science and Technology Research and Development Program Project

Open Topic of the National Railway Intelligent Transportation System Engineering Technology Research Center

Guangdong Provincial Key Area Research and Development Program Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10367982.pdf?arnumber=10367982

Reference48 articles.

1. Opportunities for multiagent systems and multiagent reinforcement learning in traffic control

2. Cooperative game-theoretic approach to traffic flow optimization for multiple intersections

3. Solving traffic queues at controlled-signalized intersections in continuous-time Markov games

4. A Distributed Assignment Method for Dynamic Traffic Assignment Using Heterogeneous-Adviser Based Multi-Agent Reinforcement Learning

5. A Novel Decentralized Game-Theoretic Adaptive Traffic Signal Controller: Large-Scale Testing

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