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TrafficPro： a framework to predict link speeds on signalized urban traffic network
更新时间：2025-05-26

    • TrafficPro： a framework to predict link speeds on signalized urban traffic network

    • “In the field of urban road network speed prediction, researchers have proposed a new framework based on generative adversarial networks and graph neural networks, which effectively improves prediction accuracy and reduces errors by 3% to 5%.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 54, Issue 8, Pages: 2214-2222(2024)
    • 作者机构：

      1.浙江大学 智能交通研究所，杭州 310058

      2.银江技术股份有限公司，杭州310023

      3.浙江工业大学 信息工程学院，杭州310023

    • DOI：10.13229/j.cnki.jdxbgxb.20221386    

      CLC： U491

    • Received：31 October 2022，

      Published：01 August 2024

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  • WEN Xiao-yue,QIAN Guo-min,KONG Hua-hua,et al.TrafficPro： a framework to predict link speeds on signalized urban traffic network[J].Journal of Jilin University(Engineering and Technology Edition),2024,54(08):2214-2222. DOI： 10.13229/j.cnki.jdxbgxb.20221386.

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