LeTS-Drive: Driving in a Crowd by Learning from Tree Search

@article{Cai2019LeTSDriveDI,
  title={LeTS-Drive: Driving in a Crowd by Learning from Tree Search},
  author={Panpan Cai and Yuanfu Luo and Aseem Saxena and David Hsu and Wee Sun Lee},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.12197}
}
Autonomous driving in a crowded environment, e.g., a busy traffic intersection, is an unsolved challenge for robotics. [...] Key Method It consists of two phases. In the offline phase, we learn a policy and the corresponding value function by imitating the belief tree search. In the online phase, the learned policy and value function guide the belief tree search. LeTS-Drive leverages the robustness of planning and the runtime efficiency of learning to enhance the performance of both. Experimental results in…Expand Abstract

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References

Publications referenced by this paper.
SHOWING 1-10 OF 34 REFERENCES

Gated Path Planning Networks

VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

PORCA: Modeling and Planning for Autonomous Driving Among Many Pedestrians

VIEW 7 EXCERPTS

Deepstack: Expertlevel artificial intelligence in heads-up no-limit poker

  • M. Moravčı́k, M. Schmid, +7 authors M. Bowling
  • Science, vol. 356, no. 6337, pp. 508–513, 2017.
  • 2017
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Intention-aware online POMDP planning for autonomous driving in a crowd

VIEW 4 EXCERPTS

Mastering the game of Go without human knowledge

VIEW 2 EXCERPTS