2 citations · 2 across the 2 of their papers we have counts for
4 papers
GuideLight: "Industrial Solution" Guidance for More Practical Traffic Signal Control Agents
Haoyuan Jiang, Xuantang Xiong, Ziyue Li +7
Currently, traffic signal control (TSC) methods based on reinforcement learning (RL) have proven superior to traditional methods. However, most RL methods face difficulties when ap…
CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control
Jingqing Ruan, Ziyue Li, Hua Wei +5
Effective multi-intersection collaboration is pivotal for reinforcement-learning-based traffic signal control to alleviate congestion. Existing work mainly chooses neighboring inte…
X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learner
Haoyuan Jiang, Ziyue Li, Hua Wei +5
The effectiveness of traffic light control has been significantly improved by current reinforcement learning-based approaches via better cooperation among multiple traffic lights.…
DuaLight: Enhancing Traffic Signal Control by Leveraging Scenario-Specific and Scenario-Shared Knowledge
Jiaming Lu, Jingqing Ruan, Haoyuan Jiang +3
Reinforcement learning has been revolutionizing the traditional traffic signal control task, showing promising power to relieve congestion and improve efficiency. However, the exis…