mlsanityData to 7 Oct 2026

CoLight: Learning Network-level Cooperation for Traffic Signal Control

arXiv 1905.05717 ↗First posted 11 May 2019cs.MA cs.GT cs.LGcited by 133

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Abstract (arXiv)

Cooperation among the traffic signals enables vehicles to move through intersections more quickly. Conventional transportation approaches implement cooperation by pre-calculating the offsets between two intersections. Such pre-calculated offsets are not suitable for dynamic traffic environments. To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication. Specifically, for a target intersection in a network, CoLight can not only incorporate the temporal and spatial influences of neighboring intersections to the target intersection, but also build up index-free modeling of neighboring intersections. To the best of our knowledge, we are the first to use graph attentional networks in the setting of reinforcement learning for traffic signal control and to conduct experiments on the large-scale road network with hundreds of traffic signals. In experiments, we demonstrate that by learning the communication, the proposed model can achieve superior performance against the state-of-the-art methods.

Key facts. Cited by 133 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 May 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 22; 2022: 18; 2023: 24; 2024: 19; 2025: 27; 2026: 23.

133 papers.

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  1. 2023LLMLight: Large Language Models as Traffic Signal Control Agentscited by 73
  2. 2023Open-TI: Open Traffic Intelligence with Augmented Language Modelcited by 38
  3. 2023Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environmentcited by 37
  4. 2023Prompt to Transfer: Sim-to-Real Transfer for Traffic Signal Control with Prompt Learningcited by 36
  5. 2025A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Modelscited by 36
  6. 2021Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal controlcited by 28
  7. 2021Efficient Pressure: Improving efficiency for signalized intersectionscited by 24
  8. 2021Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Surveycited by 23
  9. 2021The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learningcited by 23
  10. 2021Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learningcited by 20
  11. 2022LibSignal: An Open Library for Traffic Signal Controlcited by 16
  12. 2025CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Controlcited by 15
38 more
  1. 2021Reinforcement Learning for Mixed Autonomy Intersectionscited by 14
  2. 2022Unified Automatic Control of Vehicular Systems with Reinforcement Learningcited by 13
  3. 2023Reinforcement Learning Approaches for Traffic Signal Control under Missing Datacited by 13
  4. 2021Network-wide traffic signal control optimization using a multi-agent deep reinforcement learningcited by 12
  5. 2021DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Controlcited by 11
  6. 2022Multi-Agent Reinforcement Learning for Traffic Signal Control through Universal Communication Methodcited by 10
  7. 2024X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learnercited by 10
  8. 2022EMVLight: a Multi-agent Reinforcement Learning Framework for an Emergency Vehicle Decentralized Routing and Traffic Signal Control Systemcited by 9
  9. 2023DuaLight: Enhancing Traffic Signal Control by Leveraging Scenario-Specific and Scenario-Shared Knowledgecited by 9
  10. 2021A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehiclescited by 8
  11. 2021ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Controlcited by 8
  12. 2022The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Realitycited by 8
  13. 2021Leveraging Queue Length and Attention Mechanisms for Enhanced Traffic Signal Control Optimizationcited by 7
  14. 2023DenseLight: Efficient Control for Large-scale Traffic Signals with Dense Feedbackcited by 7
  15. 2023Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Controlcited by 7
  16. 2024CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Controlcited by 7
  17. 2021MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Controlcited by 6
  18. 2021Learning to Simulate on Sparse Trajectory Datacited by 6
  19. 2022CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulationcited by 6
  20. 2023Scalable Communication for Multi-Agent Reinforcement Learning via Transformer-Based Email Mechanismcited by 6
  21. 2023Large-Scale Traffic Signal Control Using Constrained Network Partition and Adaptive Deep Reinforcement Learningcited by 6
  22. 2021Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problemcited by 5
  23. 2022Model-based graph reinforcement learning for inductive traffic signal controlcited by 5
  24. 2022Reinforcement learning for traffic signal control in hybrid action spacecited by 5
  25. 2023SocialLight: Distributed Cooperation Learning towards Network-Wide Traffic Signal Controlcited by 5
  26. 2023Improving the generalizability and robustness of large-scale traffic signal controlcited by 5
  27. 2024Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphscited by 5
  28. 2024MalLight: Influence-Aware Coordinated Traffic Signal Control for Traffic Signal Malfunctionscited by 5
  29. 2025USTBench: Benchmarking and Dissecting Spatiotemporal Reasoning of LLMs as Urban Agentscited by 5
  30. 2021Multi-intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baselinecited by 4
  31. 2021Deep Reinforcement Q-Learning for Intelligent Traffic Signal Control with Partial Detectioncited by 4
  32. 2021Learning to Share in Multi-Agent Reinforcement Learningcited by 4
  33. 2024DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Datacited by 4
  34. 2025Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applicationscited by 4
  35. 2021Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systemscited by 3
  36. 2022Learning to Help Emergency Vehicles Arrive Faster: A Cooperative Vehicle-Road Scheduling Approachcited by 3
  37. 2022TinyLight: Adaptive Traffic Signal Control on Devices with Extremely Limited Resourcescited by 3
  38. 2022Feudal Multi-Agent Reinforcement Learning with Adaptive Network Partition for Traffic Signal Controlcited by 3

50 most cited of 133 All 133 (JSON)