{"url":"/task/traffic-signal-control","name":"Traffic Signal Control","slug":"traffic-signal-control","description_markdown":"Control traffic lights/signals to optimize traffic.\r\n\r\n<span style=\"color:grey; opacity: 0.6\">( Image credit: [Flaticon](https://www.flaticon.com/free-icon/traffic-light_2760947) )</span>","categories":[{"name":"Computer Code","url":"/area/computer-code"},{"name":"Miscellaneous","url":"/area/miscellaneous"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"derived"},"counts":{"papers_tagged":201,"papers_with_code":62,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":0,"subtasks":0,"parent_tasks":1},"benchmarks":[],"datasets":[],"subtasks":[],"parent_tasks":[{"url":"/task/autonomous-vehicles","name":"Autonomous Vehicles"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":62,"tagged_in_all":201,"items":[{"url":"/paper/colight-learning-network-level-cooperation","title":"CoLight: Learning Network-level Cooperation for Traffic Signal Control","date":"2019-05-11","arxiv_id":"1905.05717","repositories_listed":4,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":3}},{"url":"/paper/meta-variationally-intrinsic-motivated","title":"MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control","date":"2021-01-04","arxiv_id":"2101.00746","repositories_listed":3,"syntology":null},{"url":"/paper/illm-tsc-integration-reinforcement-learning","title":"iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvement","date":"2024-07-08","arxiv_id":"2407.06025","repositories_listed":2,"syntology":null},{"url":"/paper/learning-to-control-and-coordinate-hybrid","title":"Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections","date":"2023-01-12","arxiv_id":"2301.05294","repositories_listed":2,"syntology":null},{"url":"/paper/libsignal-an-open-library-for-traffic-signal","title":"LibSignal: An Open Library for Traffic Signal Control","date":"2022-11-19","arxiv_id":"2211.10649","repositories_listed":2,"syntology":null},{"url":"/paper/knowledge-intensive-state-design-for-traffic","title":"Leveraging Queue Length and Attention Mechanisms for Enhanced Traffic Signal Control Optimization","date":"2021-12-30","arxiv_id":"2201.00006","repositories_listed":2,"syntology":null},{"url":"/paper/efficient-pressure-improving-efficiency-for","title":"Efficient Pressure: Improving efficiency for signalized intersections","date":"2021-12-04","arxiv_id":"2112.02336","repositories_listed":2,"syntology":null},{"url":"/paper/congested-urban-networks-tend-to-be","title":"Congested Urban Networks Tend to Be Insensitive to Signal Settings: Implications for Learning-Based Control","date":"2020-08-21","arxiv_id":"2008.10989","repositories_listed":2,"syntology":null},{"url":"/paper/joint-pedestrian-and-vehicle-traffic","title":"Joint Pedestrian and Vehicle Traffic Optimization in Urban Environments using Reinforcement Learning","date":"2025-04-07","arxiv_id":"2504.05018","repositories_listed":1,"syntology":null},{"url":"/paper/a-constrained-multi-agent-reinforcement","title":"A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control","date":"2025-03-30","arxiv_id":"2503.23626","repositories_listed":1,"syntology":null},{"url":"/paper/generalized-phase-pressure-control-enhanced","title":"Generalized Phase Pressure Control Enhanced Reinforcement Learning for Traffic Signal Control","date":"2025-03-26","arxiv_id":"2503.20205","repositories_listed":1,"syntology":null},{"url":"/paper/a-parallel-hybrid-action-space-reinforcement","title":"A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control","date":"2025-03-18","arxiv_id":"2503.14250","repositories_listed":1,"syntology":null},{"url":"/paper/collmlight-cooperative-large-language-model","title":"CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control","date":"2025-03-14","arxiv_id":"2503.11739","repositories_listed":1,"syntology":null},{"url":"/paper/maclight-multi-scene-aggregation","title":"MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal Control","date":"2024-12-20","arxiv_id":"2412.15703","repositories_listed":1,"syntology":null},{"url":"/paper/difflight-a-partial-rewards-conditioned","title":"DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data","date":"2024-10-30","arxiv_id":"2410.22938","repositories_listed":1,"syntology":{"n":4,"n_ran":0,"n_unverified":4,"n_pointer_only":4}},{"url":"/paper/pytsc-a-unified-platform-for-multi-agent","title":"PyTSC: A Unified Platform for Multi-Agent Reinforcement Learning in Traffic Signal Control","date":"2024-10-23","arxiv_id":"2410.18202","repositories_listed":1,"syntology":null},{"url":"/paper/syntrac-a-synthetic-dataset-for-traffic","title":"SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras","date":"2024-08-18","arxiv_id":"2408.09588","repositories_listed":1,"syntology":null},{"url":"/paper/guidelight-industrial-solution-guidance-for","title":"GuideLight: \"Industrial Solution\" Guidance for More Practical Traffic Signal Control Agents","date":"2024-07-15","arxiv_id":"2407.10811","repositories_listed":1,"syntology":null},{"url":"/paper/a-gpu-accelerated-large-scale-simulator-for","title":"A GPU-accelerated Large-scale Simulator for Transportation System Optimization Benchmarking","date":"2024-06-15","arxiv_id":"2406.10661","repositories_listed":1,"syntology":null},{"url":"/paper/traffic-signal-cycle-control-with-centralized","title":"Traffic Signal Cycle Control with Centralized Critic and Decentralized Actors under Varying Intervention Frequencies","date":"2024-06-12","arxiv_id":"2406.08248","repositories_listed":1,"syntology":null},{"url":"/paper/coslight-co-optimizing-collaborator-selection","title":"CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control","date":"2024-05-27","arxiv_id":"2405.17152","repositories_listed":1,"syntology":null},{"url":"/paper/x-light-cross-city-traffic-signal-control","title":"X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learner","date":"2024-04-18","arxiv_id":"2404.12090","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/towards-multi-agent-reinforcement-learning-3","title":"Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphs","date":"2024-04-17","arxiv_id":"2404.11014","repositories_listed":1,"syntology":null},{"url":"/paper/llm-assisted-light-leveraging-large-language","title":"LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments","date":"2024-03-13","arxiv_id":"2403.08337","repositories_listed":1,"syntology":null},{"url":"/paper/open-ti-open-traffic-intelligence-with","title":"Open-TI: Open Traffic Intelligence with Augmented Language Model","date":"2023-12-30","arxiv_id":"2401.00211","repositories_listed":1,"syntology":{"n":8,"n_ran":5,"n_unverified":3,"n_pointer_only":8}},{"url":"/paper/large-language-models-as-traffic-signal","title":"LLMLight: Large Language Models as Traffic Signal Control Agents","date":"2023-12-26","arxiv_id":"2312.16044","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/dualight-enhancing-traffic-signal-control-by","title":"DuaLight: Enhancing Traffic Signal Control by Leveraging Scenario-Specific and Scenario-Shared Knowledge","date":"2023-12-22","arxiv_id":"2312.14532","repositories_listed":1,"syntology":null},{"url":"/paper/feedback-feedforward-signal-control-with","title":"Feedback-feedforward Signal Control with Exogenous Demand Estimation in Congested Urban Road Networks","date":"2023-12-12","arxiv_id":"2312.07359","repositories_listed":1,"syntology":null},{"url":"/paper/traffic-signal-control-using-lightweight","title":"Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL Approach","date":"2023-12-12","arxiv_id":"2312.07795","repositories_listed":1,"syntology":null},{"url":"/paper/unitsa-a-universal-reinforcement-learning","title":"UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control","date":"2023-12-08","arxiv_id":"2312.05090","repositories_listed":1,"syntology":null}],"syntology_records":5,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}