Datasets › LemgoRL

LemgoRL

Introduced by Arthur Müller et al. in Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control30 Mar 2021 archive 2025-07-28

LemgoRL is an open-source benchmark tool for traffic signal control designed to train reinforcement learning agents in a highly realistic simulation scenario with the aim to reduce Sim2Real gap. In addition to the realistic simulation model, LemgoRL encompasses a traffic signal logic unit that ensures compliance with all regulatory and safety requirements. LemgoRL offers the same interface as the well-known OpenAI gym toolkit to enable easy deployment in existing research work.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 4 papers for it but never published that list.

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

GNU GPL V3.0 License

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • LemgoRL

1 variant name, as the archive lists them.

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