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Research on spatio-temporal network prediction model of parallel–series traffic flow based on Transformer and GCAT

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  • Zhu, Changfeng
  • Yu, Chunxiao
  • Huo, Jiuyuan

Abstract

Traffic flow forecasting is critical in transportation research. However, the excessive nonlinearity and complexity of spatial and temporal correlations in traffic flow critically restrict the prediction accuracy. To cope with the challenge, a parallel–series combined deep learning prediction model is proposed. Firstly, the traffic flow data is decomposed into unique time spans consistent with positive rules (weekly, daily, and hourly cycles). Then, a deep learning model named Transformer-Graph Convolutional Attention Networks (TRGCAT) is further used to predict the multi-flow in the traffic network. TRGCAT firstly encodes and concatenates the current hourly, daily, and weekly periodic features of all traffic nodes in parallel, which decodes the middle output with spatial features, and ultimately predicts future single-step, short-term, and long-term multi-step traffic flow by using Graph Convolutional Attention Network (GCAT) in series. We conduct numerical experiments on open-source datasets PeMS, the results show that TRGCAT does better in spatial and temporal fusion and may acquire extra aggressive forecasting consequences than baseline methods.

Suggested Citation

  • Zhu, Changfeng & Yu, Chunxiao & Huo, Jiuyuan, 2023. "Research on spatio-temporal network prediction model of parallel–series traffic flow based on Transformer and GCAT," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    • Handle: RePEc:eee:phsmap:v:610:y:2023:i:c:s0378437122009724
    DOI: 10.1016/j.physa.2022.128414
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    1. Kleijnen, J.P.C., 1999. "Validation of Models : Statistical Techniques and Data Availability," Other publications TiSEM f7518d14-a5e9-4c69-a579-6, Tilburg University, School of Economics and Management.
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    Cited by:

    1. Ma, Changxi & Zhao, Mingxi, 2023. "Spatio-temporal multi-graph convolutional network based on wavelet analysis for vehicle speed prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).

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