Agent-based optimization for multiple signalized intersections using Q-learning
Relieving urban traffic congestion has always been an urgent call in a dynamic traffic network. The objective of this research is to control the traffic flow within a traffic network consists of multiple signalized intersections with traffic ramp. The massive traffic network problem is dealt through...
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| Format: | Article |
| Language: | English English |
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United Kingdom Simulation Society
2014
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| Online Access: | https://eprints.ums.edu.my/id/eprint/29138/1/Agent-based%20optimization%20for%20Multiple%20Signalized%20Intersections%20using%20Q-Learning%20ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/29138/2/Agent-Based%20Optimization%20for%20Multiple%20Signalized%20Intersections%20using%20Q-Learning_FULL%20TEXT.pdf |
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| author | Teo, Kenneth Tze Kin Yeo Kiam Beng @ Abdul Noor Chin, Yit Kwong Chuo, Helen Sin Ee Tan, Min Keng |
| author_facet | Teo, Kenneth Tze Kin Yeo Kiam Beng @ Abdul Noor Chin, Yit Kwong Chuo, Helen Sin Ee Tan, Min Keng |
| author_sort | Teo, Kenneth Tze Kin |
| collection | UMS |
| description | Relieving urban traffic congestion has always been an urgent call in a dynamic traffic network. The objective of this research is to control the traffic flow within a traffic network consists of multiple signalized intersections with traffic ramp. The massive traffic network problem is dealt through Q-learning actuated traffic signalization (QLTS), where the traffic phases will be monitored as immediate actions can be taken during congestion to minimize the number of vehicles in queue. QLTS is tested under two cases and has better performance than common fixed-time traffic signalization (FTS). When dealing with the ramp flow, QLTS has flexibility to change the traffic signals according to the traffic conditions and necessity. |
| first_indexed | 2024-03-06T03:08:39Z |
| format | Article |
| id | ums.eprints-29138 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:08:39Z |
| publishDate | 2014 |
| publisher | United Kingdom Simulation Society |
| record_format | dspace |
| spelling | ums.eprints-291382021-09-10T06:56:32Z https://eprints.ums.edu.my/id/eprint/29138/ Agent-based optimization for multiple signalized intersections using Q-learning Teo, Kenneth Tze Kin Yeo Kiam Beng @ Abdul Noor Chin, Yit Kwong Chuo, Helen Sin Ee Tan, Min Keng QA76.75-76.765 Computer software TE1-450 Highway engineering. Roads and pavements Relieving urban traffic congestion has always been an urgent call in a dynamic traffic network. The objective of this research is to control the traffic flow within a traffic network consists of multiple signalized intersections with traffic ramp. The massive traffic network problem is dealt through Q-learning actuated traffic signalization (QLTS), where the traffic phases will be monitored as immediate actions can be taken during congestion to minimize the number of vehicles in queue. QLTS is tested under two cases and has better performance than common fixed-time traffic signalization (FTS). When dealing with the ramp flow, QLTS has flexibility to change the traffic signals according to the traffic conditions and necessity. United Kingdom Simulation Society 2014 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/29138/1/Agent-based%20optimization%20for%20Multiple%20Signalized%20Intersections%20using%20Q-Learning%20ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/29138/2/Agent-Based%20Optimization%20for%20Multiple%20Signalized%20Intersections%20using%20Q-Learning_FULL%20TEXT.pdf Teo, Kenneth Tze Kin and Yeo Kiam Beng @ Abdul Noor and Chin, Yit Kwong and Chuo, Helen Sin Ee and Tan, Min Keng (2014) Agent-based optimization for multiple signalized intersections using Q-learning. International Journal of Simulation: Systems, Science & Technology (IJSSST), 15. pp. 90-96. ISSN 1473-8031 (P-ISSN) , 1473-804x (E-ISSN) https://ijssst.info/Vol-15/No-6/paper10.pdf http://dx.doi.org/10.5013/IJSSST.a.15.06.10 http://dx.doi.org/10.5013/IJSSST.a.15.06.10 |
| spellingShingle | QA76.75-76.765 Computer software TE1-450 Highway engineering. Roads and pavements Teo, Kenneth Tze Kin Yeo Kiam Beng @ Abdul Noor Chin, Yit Kwong Chuo, Helen Sin Ee Tan, Min Keng Agent-based optimization for multiple signalized intersections using Q-learning |
| title | Agent-based optimization for multiple signalized intersections using Q-learning |
| title_full | Agent-based optimization for multiple signalized intersections using Q-learning |
| title_fullStr | Agent-based optimization for multiple signalized intersections using Q-learning |
| title_full_unstemmed | Agent-based optimization for multiple signalized intersections using Q-learning |
| title_short | Agent-based optimization for multiple signalized intersections using Q-learning |
| title_sort | agent based optimization for multiple signalized intersections using q learning |
| topic | QA76.75-76.765 Computer software TE1-450 Highway engineering. Roads and pavements |
| url | https://eprints.ums.edu.my/id/eprint/29138/1/Agent-based%20optimization%20for%20Multiple%20Signalized%20Intersections%20using%20Q-Learning%20ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/29138/2/Agent-Based%20Optimization%20for%20Multiple%20Signalized%20Intersections%20using%20Q-Learning_FULL%20TEXT.pdf |
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