The invention discloses a traffic flow prediction method based on time-space synchronization GraphSAGE. The method comprises the following steps: generating traffic flow data of a time sequence; according to the spatial adjacency matrix and the Spearman correlation coefficient matrix, firstly constructing an inclusive spatial adjacency matrix, and then designing an inclusive space-time synchronization diagram; according to the method, a space-time synchronization GraphSAGE model is constructed, traffic characteristics of space-time neighbors from 1 order to K order are aggregated through an attention mechanism for each traffic node according to a GraphSAGE thought, and the traffic characteristics are spliced with the characteristics of the traffic node, so that space-time dependence of traffic flow data is synchronously learned in an inductive manner. According to the method, space-time synchronous modeling of the traffic flow data is realized by designing the inclusive space-time synchronous graph, so that the model achieves accurate prediction precision, and meanwhile, the limitation of full-graph training and direct-push learning in the conventional traffic flow prediction method is solved based on the space-time characteristics of the GraphSAGE inductive aggregation traffic nodes.

    本发明公开了一种基于时空同步GraphSAGE的交通流量预测方法,包括:生成时间序列的交通流数据;根据空间邻接矩阵和斯皮尔曼相关系数矩阵,先构建包容式空间邻接矩阵,进而设计包容式时空同步图;构建时空同步GraphSAGE模型,该模型依照GraphSAGE思想,对每个交通节点,通过注意力机制聚合其1到K阶时空邻居的交通特征,并与该交通节点的本身特征进行拼接,以此归纳式同步学习交通流数据的时空依赖。本发明通过设计包容式时空同步图,实现交通流数据的时空同步建模,使模型达到精确的预测精度,同时基于GraphSAGE归纳式聚合交通节点的时空特征,解决了以往交通流量预测方法中全图训练及直推式学习的局限性。


    Access

    Download


    Export, share and cite



    Title :

    Traffic flow prediction method based on space-time synchronization GraphSAGE


    Additional title:

    一种基于时空同步GraphSAGE的交通流量预测方法


    Contributors:
    SHI QUAN (author) / YU XIAN (author) / BAO YINXIN (author)

    Publication date :

    2024-11-26


    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



    Space-time synchronization traffic flow prediction method based on fusion type GraphSAGE

    SHI QUAN / YU XIAN / BAO YINXIN | European Patent Office | 2024

    Free access

    GraphSAGE-GAN-based traffic network data restoration method

    XU DONGWEI / WEI CHENCHEN / DING JIALI et al. | European Patent Office | 2021

    Free access


    GraphSAGE-Based Traffic Speed Forecasting for Segment Network With Sparse Data

    Liu, Jielun / Ong, Ghim Ping / Chen, Xiqun | IEEE | 2022


    Traffic flow prediction method based on dynamic multi-graph space-time synchronization network

    SHI QUAN / YU XIAN / BAO YINXIN | European Patent Office | 2024

    Free access