• Corpus ID: 226227290

Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RL

@article{Vinitsky2020OptimizingMA,
  title={Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RL},
  author={Eugene Vinitsky and Nathan Lichtl{\'e} and Kanaad Parvate and Alexandre M. Bayen},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.00120}
}
We study the ability of autonomous vehicles to improve the throughput of a bottleneck using a fully decentralized control scheme in a mixed autonomy setting. We consider the problem of improving the throughput of a scaled model of the San Francisco-Oakland Bay Bridge: a two-stage bottleneck where four lanes reduce to two and then reduce to one. Although there is extensive work examining variants of bottleneck control in a centralized setting, there is less study of the challenging multi-agent… 
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