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Roadway Capacity-driven Graph Convolution Network for Network-Wide Traffic Prediction

The Roadway Capacity-driven Graph Convolution Network (RCDGCN) model integrates static and dynamic roadway capacity attributes in spatio-temporal settings to predict network-wide traffic states.

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Cite this as

Zilin Bian, Jingqin Gao, Kaan Ozbay, Fan Zuo, Dachuan Zuo, Zhenning Li (2024). Dataset: Roadway Capacity-driven Graph Convolution Network for Network-Wide Traffic Prediction. https://doi.org/10.57702/4jvow8k6

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Additional Info

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Created December 2, 2024
Last update December 2, 2024
Author Zilin Bian
More Authors
Jingqin Gao
Kaan Ozbay
Fan Zuo
Dachuan Zuo
Zhenning Li