Skip to content
Computational framework for reinforcement learning in traffic control
Branch: master
Clone or download
Pull request Compare This branch is 14 commits behind flow-project:master.
nathanlct Merge pull request flow-project#648 from flow-project/k_closest_to_in…
…tersection

Add padding and docstring to `green_wave_env.k_closest_to_intersection`
Latest commit dc91f90 Jul 18, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.github Fixed minor typos Jul 7, 2019
docs Multi-agent traffic light grid (flow-project#623) Jul 16, 2019
examples Multi-agent traffic light grid (flow-project#623) Jul 16, 2019
flow Merge pull request flow-project#648 from flow-project/k_closest_to_in… Jul 18, 2019
scripts Merge pull request flow-project#607 from flow-project/v0.4.0 Jul 14, 2019
tests fix pep8 Jul 18, 2019
tutorials fix code typo Jul 9, 2019
.coveragerc
.gitignore add all Aimsun secondary files to .gitignore Jun 2, 2019
.readthedocs.yml modifications to support autodoc in readthedocs Jan 23, 2019
.travis.yml optimize order Jul 15, 2019
CODEOWNERS Updating tutorial (flow-project#3) Oct 13, 2017
CODE_OF_CONDUCT.md Create CODE_OF_CONDUCT.md Apr 23, 2019
Dockerfile Add Dockerfile for release 0.3.0 and remove outdated docker folder. Mar 8, 2019
LICENSE.md added MIT license Oct 11, 2017
Makefile.template Flow initial release (#1) Oct 5, 2017
README.md Add experimental binder logo. Jul 1, 2019
environment.yml updated setup instructions Mar 31, 2019
requirements.txt updated setup instructions Mar 31, 2019
setup.py Merge pull request flow-project#607 from flow-project/v0.4.0 Jul 14, 2019

README.md

Build Status Docs Coverage Status Binder License

Flow

Flow is a computational framework for deep RL and control experiments for traffic microsimulation.

See our website for more information on the application of Flow to several mixed-autonomy traffic scenarios. Other results and videos are available as well.

More information

Technical questions

Please direct your techincal questions to Stack Overflow using the flow-project tag.

Getting involved

We welcome your contributions.

Citing Flow

If you use Flow for academic research, you are highly encouraged to cite our paper:

C. Wu, A. Kreidieh, K. Parvate, E. Vinitsky, A. Bayen, "Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control," CoRR, vol. abs/1710.05465, 2017. [Online]. Available: https://arxiv.org/abs/1710.05465

If you use the benchmarks, you are highly encouraged to cite our paper:

Vinitsky, E., Kreidieh, A., Le Flem, L., Kheterpal, N., Jang, K., Wu, F., ... & Bayen, A. M. (2018, October). Benchmarks for reinforcement learning in mixed-autonomy traffic. In Conference on Robot Learning (pp. 399-409).

Contributors

Flow is supported by the Mobile Sensing Lab at UC Berkeley and Amazon AWS Machine Learning research grants. The contributors are listed in Flow Team Page.

You can’t perform that action at this time.