{"id":13723914,"url":"https://github.com/cityflow-project/CityFlow","last_synced_at":"2025-05-07T17:31:49.519Z","repository":{"id":37664790,"uuid":"172636772","full_name":"cityflow-project/CityFlow","owner":"cityflow-project","description":"A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario","archived":false,"fork":false,"pushed_at":"2022-02-17T14:45:39.000Z","size":340,"stargazers_count":792,"open_issues_count":40,"forks_count":173,"subscribers_count":19,"default_branch":"master","last_synced_at":"2024-11-12T23:36:24.602Z","etag":null,"topics":["multiagent-reinforcement-learning","multiagent-systems","traffic-signal-control","traffic-simulation"],"latest_commit_sha":null,"homepage":"https://cityflow-project.github.io","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cityflow-project.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-02-26T04:16:52.000Z","updated_at":"2024-11-09T02:57:55.000Z","dependencies_parsed_at":"2022-07-12T16:42:40.053Z","dependency_job_id":null,"html_url":"https://github.com/cityflow-project/CityFlow","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cityflow-project%2FCityFlow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cityflow-project%2FCityFlow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cityflow-project%2FCityFlow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cityflow-project%2FCityFlow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cityflow-project","download_url":"https://codeload.github.com/cityflow-project/CityFlow/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224378208,"owners_count":17301273,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["multiagent-reinforcement-learning","multiagent-systems","traffic-signal-control","traffic-simulation"],"created_at":"2024-08-03T01:01:47.107Z","updated_at":"2024-11-14T13:31:09.907Z","avatar_url":"https://github.com/cityflow-project.png","language":"C++","funding_links":[],"categories":["Consumption"],"sub_categories":["Mobility and Transportation"],"readme":"CityFlow\n============\n\n.. image:: https://readthedocs.org/projects/cityflow/badge/?version=latest\n    :target: https://cityflow.readthedocs.io/en/latest/?badge=latest\n    :alt: Documentation Status\n\n.. image:: https://dev.azure.com/CityFlow/CityFlow/_apis/build/status/cityflow-project.CityFlow?branchName=master\n    :target: https://dev.azure.com/CityFlow/CityFlow/_build/latest?definitionId=2\u0026branchName=master\n    :alt: Build Status\n\nCityFlow is a multi-agent reinforcement learning environment for large-scale city traffic scenario.\n\nCheckout these features!\n\n- A microscopic traffic simulator which simulates the behavior of each vehicle, providing highest level detail of traffic evolution.\n- Supports flexible definitions for road network and traffic flow\n- Provides friendly python interface for reinforcement learning\n- **Fast!** Elaborately designed data structure and simulation algorithm with multithreading. Capable of simulating city-wide traffic. See the performance comparison with SUMO [#sumo]_.\n\n.. figure:: https://user-images.githubusercontent.com/44251346/54403537-5ce16b00-470b-11e9-928d-76c8ba0ab463.png\n    :align: center\n    :alt: performance compared with SUMO\n\n    Performance comparison between CityFlow with different number of threads (1, 2, 4, 8) and SUMO. From small 1x1 grid roadnet to city-level 30x30 roadnet. Even faster when you need to interact with the simulator through python API.\n\nScreencast\n----------\n\n.. figure:: https://user-images.githubusercontent.com/44251346/62375390-c9e98600-b570-11e9-8808-e13dbe776f1e.gif\n    :align: center\n    :alt: demo\n\nFeatured Research and Projects Using CityFlow\n---------------------------------------------\n- `PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network (KDD 2019) \u003chttp://personal.psu.edu/hzw77/publications/presslight-kdd19.pdf\u003e`_\n- `CoLight: Learning Network-level Cooperation for Traffic Signal Control \u003chttps://arxiv.org/abs/1905.05717\u003e`_\n- `Traffic Signal Control Benchmark \u003chttps://traffic-signal-control.github.io/\u003e`_\n- `TSCC2050: A Traffic Signal Control Game by Tianrang Intelligence (in Chinese) \u003chttp://game.tscc2050.com/\u003e`_ [#tianrang]_\n\nLinks\n-----\n\n- `WWW 2019 Demo Paper \u003chttps://arxiv.org/abs/1905.05217\u003e`_\n- `Home Page \u003chttp://cityflow-project.github.io/\u003e`_\n- `Documentation and Quick Start \u003chttps://cityflow.readthedocs.io/en/latest/\u003e`_\n- `Docker \u003chttps://hub.docker.com/r/cityflowproject/cityflow\u003e`_\n\n\n.. [#sumo] `SUMO home page \u003chttps://sumo.dlr.de/index.html\u003e`_\n.. [#tianrang] `Tianrang Intelligence home page \u003chttps://www.tianrang.com/\u003e`_\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcityflow-project%2FCityFlow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcityflow-project%2FCityFlow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcityflow-project%2FCityFlow/lists"}