Multi-agent Traffic Light Controls with SUMO

Author:

Phon-Amnuaisuk Somnuk1,Tan Soon-Jiann2,Yap Yok-Hoe2,Choong Florence Chiao-Mei3,Vejjanugraha Pikul4,Khor Kok-Chin5,Ng Keng-Hoong6

Affiliation:

1. School of Computing and Informatics, Universiti Teknologi Brunei,Gadong,Brunei

2. Universiti Teknologi Brunei,Faculty of Engineering,Gadong,Brunei

3. School of Engineering and Physical Sciences, Heriot-Watt University,Malaysia Campus,Malaysia

4. Thai-Nichi Institute of Technology,Department of International College,Thailand

5. Universiti Tunku Abdul Rahman,LKC Faculty of Engineering and Science,Malaysia

6. School of Computing, Asia Pacific University of Technology and Innovation,Malaysia

Publisher

IEEE

Reference19 articles.

1. Traffic flow optimization: A reinforcement learning approach

2. Modeling Isolated Traffic Control Strategies in TraffSim

3. Cooperative Multi-agent Control Using Deep Reinforcement Learning

4. An overview of agent-based traffic simulators;johannes;Transportation Research Interdisciplinary Perspectives,2021

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Reinforcement Learning Approach to Adaptive Traffic Signal Control Using SUMO-RL;2024 25th International Carpathian Control Conference (ICCC);2024-05-22

2. An Optimal Re-parametrization Scheme for Generalization in Reinforcement Learning;2023 14th International Conference on Information and Communication Technology Convergence (ICTC);2023-10-11

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