{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/colight-learning-network-level-cooperation","title":"CoLight: Learning Network-level Cooperation for Traffic Signal Control","arxiv_id":"1905.05717","date":"2019-05-11","proceeding":null,"authors":["Hua Wei","Nan Xu","Huichu Zhang","Guanjie Zheng","Xinshi Zang","Chacha Chen","Wei-Nan Zhang","Yanmin Zhu","Kai Xu","Zhenhui Li"],"abstract":"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.","url_abs":"https://arxiv.org/abs/1905.05717v2","url_pdf":"https://arxiv.org/pdf/1905.05717v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"colight-learning-network-level-cooperation","repo_url":"https://github.com/wingsweihua/colight","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null},{"paper_slug":"colight-learning-network-level-cooperation","repo_url":"https://github.com/PKU-AI-Edge/DGN/","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"colight-learning-network-level-cooperation","repo_url":"https://github.com/cityflow-project/CityFlow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"colight-learning-network-level-cooperation","repo_url":"https://github.com/cityflow-project/cityflower","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"multi-agent-reinforcement-learning","task_name":"Multi-agent Reinforcement Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"traffic-signal-control","task_name":"Traffic Signal Control"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1905.05717","atlas_url":"https://app.syntology.ai/?focus=1905.05717","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.05717"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/wingsweihua/colight","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/cityflow-project/cityflower","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/cityflow-project/CityFlow","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/PKU-AI-Edge/DGN/","reach":{"status":"ok"}}],"summary":{"ran_honours":1,"ran_draft_wrong":2},"by_repo_kind":{"official":{"samples":3,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":3,"samples":[{"code_sha256_prefix":"17ee49d590baac51","entry":"check_all_workers_working","repo":"wingsweihua/colight","repo_kind":"official","path":"runexp.py","file_url":"https://github.com/wingsweihua/colight/blob/HEAD/runexp.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"17ee49d590baac51"}},{"code_sha256_prefix":"7c54e206b2877818","entry":"memo_rename","repo":"wingsweihua/colight","repo_kind":"official","path":"runexp.py","file_url":"https://github.com/wingsweihua/colight/blob/HEAD/runexp.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"7c54e206b2877818"}},{"code_sha256_prefix":"c2283faa90c2a217","entry":"merge","repo":"wingsweihua/colight","repo_kind":"official","path":"runexp.py","file_url":"https://github.com/wingsweihua/colight/blob/HEAD/runexp.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c2283faa90c2a217"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}