The invention discloses a traffic flow prediction method based on a cyclic attention coupled graph convolutional network. The method comprises the following steps of 1) constructing a traffic flow time sequence according to traffic flow data collected by road coil sensors on an urban traffic road network, and preprocessing the traffic flow time sequence; 2) constructing a coupled graph to represent a spatial dependency relationship, wherein the coupled graph comprises a node graph and an edge graph, a single sensor is regarded as a node, the node graph is constructed according to the road network distance between the sensors, edges in the node graph represent the relationship between the sensors, the edges in the node graph are regarded as nodes to construct the edge graph, and the edges in the edge graph represent mutual influence of the relationship between the sensors; and 3) inputting the preprocessed traffic flow time sequence into the cyclic attention coupled graph convolutionalnetwork to predict the traffic flow of the future traffic road network. The traffic flow prediction method can predict the traffic flow of the traffic road network, and has a wide application prospectin the fields of travel planning, traffic management and the like.

    本发明公开了一种基于循环注意力对偶图卷积网络的交通流量预测方法,包括:1)根据城市交通路网上道路线圈传感器所采集的车流数据构建交通流量时序,并进行预处理;2)构建对偶图表示空间依赖关系,对偶图包含节点图和边图,其中,将单个传感器视作节点,根据传感器之间的路网距离构建节点图,节点图中的边表示传感器间的关系,将节点图中的边视作节点构建边图,边图中的边表示传感器间关系的互相影响;3)将预处理后的交通流量时序输入循环注意力对偶图卷积网络中,预测未来交通路网的交通流量。该交通流量预测方法能够实现对交通路网的交通流量进行预测,在出行规划、交通管理等领域都具有广阔的应用前景。


    Access

    Download


    Export, share and cite



    Title :

    Traffic flow prediction method based on cyclic attention coupled graph convolutional network


    Additional title:

    一种基于循环注意力对偶图卷积网络的交通流量预测方法


    Contributors:
    CHEN LING (author) / CHEN WEIQI (author)

    Publication date :

    2020-05-01


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



    Traffic flow prediction method based on self-attention mechanism and cyclic graph convolutional network

    MENG XIANWEI / LU YIXING / JIA LIN | European Patent Office | 2023

    Free access

    Traffic flow prediction method based on de-noising attention enhancement cyclic multi-graph convolutional network

    SHI QUAN / BAO YINXIN / SHEN QINQIN et al. | European Patent Office | 2024

    Free access

    Traffic flow prediction method based on time attention circulation graph convolutional neural network

    FAN WENDONG / SHU MIN / SONG YUN et al. | European Patent Office | 2023

    Free access

    Attention-Based Spatiotemporal Adaptive Graph Diffusion Convolutional Network For Traffic Flow Prediction

    He, Qiansong / Xia, Dawen / Li, Jianjun et al. | Transportation Research Record | 2025


    Traffic flow prediction method based on graph convolutional network

    XU HUI / MENG FANYU / REN QIANQIAN et al. | European Patent Office | 2025

    Free access