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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
| Date | Stars |
|---|---|
| 2026-07-31 | 1009 |
| 2026-08-03 | 1008 |
| 2026-08-06 | 1008 |
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— stars today
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Momentum
0.0
growth rate 0.00%/day
CityFlow
============
.. image:: https://readthedocs.org/projects/cityflow/badge/?version=latest
:target: https://cityflow.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://dev.azure.com/CityFlow/CityFlow/_apis/build/status/cityflow-project.CityFlow?branchName=master
:target: https://dev.azure.com/CityFlow/CityFlow/_build/latest?definitionId=2&branchName=master
:alt: Build Status
CityFlow is a multi-agent reinforcement learning environment for large-scale city traffic scenario.
Checkout these features!
- A microscopic traffic simulator which simulates the behavior of each vehicle, providing highest level detail of traffic evolution.
- Supports flexible definitions for road network and traffic flow
- Provides friendly python interface for reinforcement learning
- **Fast!** Elaborately designed data structure and simulation algorithm with multithreading. Capable of simulating city-wide traffic. See the performance comparison with SUMO [#sumo]_.
.. figure:: https://user-images.githubusercontent.com/44251346/54403537-5ce16b00-470b-11e9-928d-76c8ba0ab463.png
:align: center
:alt: performance compared with SUMO
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.
Screencast
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.. figure:: https://user-images.githubusercontent.com/44251346/62375390-c9e98600-b570-11e9-8808-e13dbe776f1e.gif
:align: center
:alt: demo
Featured Research and Projects Using CityFlow
---------------------------------------------
- `PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network (KDD 2019) <http://personal.psu.edu/hzw77/publications/presslight-kdd19.pdf>`_
- `CoLight: Learning Network-level Cooperation for Traffic Signal Control <https://arxiv.org/abs/1905.05717>`_
- `Traffic Signal Control Benchmark <https://traffic-signal-control.github.io/>`_
- `TSCC2050: A Traffic Signal Control Game by Tianrang Intelligence (in Chinese) <http://game.tscc2050.com/>`_ [#tianrang]_
Links
-----
- `WWW 2019 Demo Paper <https://arxiv.org/abs/1905.05217>`_
- `Home Page <http://cityflow-project.github.io/>`_
- `Documentation and Quick Start <https://cityflow.readthedocs.io/en/latest/>`_
- `Docker <https://hub.docker.com/r/cityflowproject/cityflow>`_
.. [#sumo] `SUMO home page <https://sumo.dlr.de/index.html>`_
.. [#tianrang] `Tianrang Intelligence home page <https://www.tianrang.com/>`_
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Isaac Lee · Google · United States
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Weinan Zhang · Shanghai Jiao Tong University · China
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:f44b2228215d3a58, desc:multi-agent, desc:multi agent