Towards fair lights:A multi-agent masked deep reinforcement learning for efficient corridor-level traffic signal controlOA
Towards fair lights:A multi-agent masked deep reinforcement learning for efficient corridor-level traffic signal control
Xiaocai Zhang;Lok Sang Chan;Neema Nassir;Majid Sarvi
Department of Infrastructure Engineering,Faculty of Engineering and Information Technology,The University of Melbourne,Melbourne,3010,AustraliaDepartment of Infrastructure Engineering,Faculty of Engineering and Information Technology,The University of Melbourne,Melbourne,3010,AustraliaDepartment of Infrastructure Engineering,Faculty of Engineering and Information Technology,The University of Melbourne,Melbourne,3010,AustraliaDepartment of Infrastructure Engineering,Faculty of Engineering and Information Technology,The University of Melbourne,Melbourne,3010,Australia
Adaptive traffic signal control(ATSC)Multi-agentFairnessDeep reinforcement learning(DRL)Mask
Adaptive traffic signal control(ATSC)Multi-agentFairnessDeep reinforcement learning(DRL)Mask
《交通研究通讯（英文）》 2025 (3)
164-177,14
This work was funded by ARC(Grant No.LP200301389),Kapsch TrafficCom Australia,RACQ,and iMOVE CRC,the Cooperative Research Centres program,an Australian Government initiative.
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