The invention discloses a road section traffic congestion prediction method and system, belongs to the technical field of data processing, and aims to solve the technical problem of how to accurately judge and predict the congestion condition of road section traffic in real time. Comprising the following steps: acquiring a traffic video in real time for a target road section; taking the real-time traffic video as a target video, and performing data preprocessing on the target video to obtain a preprocessed traffic video image; based on a computer vision technology, extracting road section traffic features from the target video image; a traffic jam prediction model is constructed based on a convolutional neural network, and the traffic jam prediction model uses the road section traffic features as input to predict and output a jam label value in a future predetermined time period; and by taking the road section traffic characteristics as input, analyzing and predicting the traffic of the current road section through the trained traffic jam prediction model, and outputting a traffic jam label value in a future predetermined time period.

    本发明公开了路段交通拥堵预测方法及系统,属于数据处理技术领域,要解决的技术问题为如何实时准确的对路段交通的拥堵情况进行判断预测。包括如下步骤:对于目标路段,实时采集交通视频;将实时交通视频为目标视频,对目标视频进行数据预处理,得到预处理后交通视频图像;基于计算机视觉技术,从目标视频图像中提取路段交通特征;基于卷积神经网络构建交通拥堵预测模型,所述交通拥堵预测模型以路段交通特征为输入、预测输出未来预定时段的拥堵标签值;以路段交通特征为输入、通过训练后的交通拥堵预测模型对当前路段交通进行分析和预测,输出未来预定时段的交通拥堵标签值。


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    Title :

    Road section traffic jam prediction method and system


    Additional title:

    路段交通拥堵预测方法及系统


    Contributors:
    FU HAIYANG (author)

    Publication date :

    2023-10-13


    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 / G06V



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