• Corpus ID: 237513888

Back to Basics: Deep Reinforcement Learning in Traffic Signal Control

@article{Kanis2021BackTB,
  title={Back to Basics: Deep Reinforcement Learning in Traffic Signal Control},
  author={Sierk Kanis and Laurens Samson and Daan Bloembergen and Tim Bakker},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.07180}
}
In this paper we revisit some of the fundamental premises for a reinforcement learning (RL) approach to self-learning traffic lights. We propose RLight, a combination of choices that offers robust performance and good generalization to unseen traffic flows. In particular, ourmain contributions are threefold: our lightweight and cluster-aware state representation leads to improved performance; we reformulate the Markov Decision Process (MDP) such that it skips redundant timesteps of yellow light… 

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References

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