The invention discloses a traffic jam prediction method based on a graph neural network, and belongs to the field of target detection, and the method comprises the following steps: constructing an urban traffic monitoring graph structure, and collecting monitoring video data; monitoring video data are collected, and the monitoring video data comprise video data of different periods; performing target detection on the monitoring video data to obtain a traffic attribute and an abnormal event sequence; and based on the urban traffic monitoring graph structure, adopting a graph neural network to carry out traffic jam prediction on the traffic attributes and the abnormal event sequence to obtain a prediction result of the monitor.

    本发明公开了一种基于图神经网络的交通拥堵预测方法,属于目标检测领域,该方法包括以下步骤:构建城市交通监控图结构并采集监控视频数据;采集监控视频数据,其中,所述监控视频数据包括不同周期的视频数据;对所述监控视频数据进行目标检测得到交通属性和异常事件序列;基于所述城市交通监控图结构采用图神经网络对所述交通属性和异常事件序列进行交通拥堵预测得到监控器的预测结果。


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    Title :

    Traffic jam prediction method based on graph neural network


    Additional title:

    一种基于图神经网络的交通拥堵预测方法


    Contributors:
    YANG YANG (author) / WANG SHIJI (author)

    Publication date :

    2024-08-30


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06V / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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