Agent-based optimization for multiple signalized intersections using Q-learning

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)

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URL: https://ijssst.info/Vol-15/No-6/paper10.pdf

Abstract

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.

Item Type:	Article
Keyword:	Disturbance , Multi-agent , Q-learning , Traffic signalization , Traffic flow optimization
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software T Technology > TE Highway engineering. Roads and pavements > TE1-450 Highway engineering. Roads and pavements
Department:	FACULTY > Faculty of Engineering
Depositing User:	SAFRUDIN BIN DARUN -
Date Deposited:	10 Sep 2021 14:56
Last Modified:	10 Sep 2021 14:56
URI:	https://eprints.ums.edu.my/id/eprint/29138

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