DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control

@article{Wu2021DynSTGATDS,
  title={DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control},
  author={Libing Wu and Min Wang and Dan Wu and Jia Wu},
  journal={Proceedings of the 30th ACM International Conference on Information \& Knowledge Management},
  year={2021}
}
  • Libing Wu, Min Wang, +1 author Jia Wu
  • Published 12 September 2021
  • Computer Science
  • Proceedings of the 30th ACM International Conference on Information & Knowledge Management
Adaptive traffic signal control plays a significant role in the construction of smart cities. This task is challenging because of many essential factors, such as cooperation among neighboring intersections and dynamic traffic scenarios. First, to facilitate the cooperation of traffic signals, existing work adopts graph neural networks to incorporate the temporal and spatial influences of the surrounding intersections into the target intersection, where spatial-temporal information is usedโ€ฆย Expand

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