The invention discloses a road transfer traffic volume prediction method based on a discrete selection model, and the method comprises the steps: obtaining the environment data of a target road, collecting the environment data and traffic data of a traffic network, and building a traffic network model; performing dynamic time window division on the traffic data to obtain window data, and predicting the window data to obtain predicted window data; performing influence analysis on the window data based on the environment data to obtain an environment selection probability, and obtaining a predicted road transfer traffic volume based on a discrete selection model according to the predicted window data and the environment selection probability; and constructing a road transfer traffic volume prediction model according to the predicted road transfer traffic volume, inputting to-be-analyzed road data into the road transfer traffic volume prediction model, and outputting a prediction result. The method not only can improve the precision of road transfer traffic volume prediction, but also has good interpretability, and can be directly applied to a road transfer traffic volume prediction system.

    本发明公开了一种基于离散选择模型的公路转移交通量预测方法,包括:获取目标公路的环境数据,采集交通网络的环境数据和交通数据,建立交通网络模型;对所述交通数据进行动态时间窗划分得到窗口数据,对所述窗口数据进行预测得到预测窗口数据;基于所述环境数据对所述窗口数据进行影响分析得到环境选择概率,根据所述预测窗口数据和所述环境选择概率基于离散选择模型得到预测公路转移交通量;根据所述预测公路转移交通量构建公路转移交通量预测模型,将待分析公路数据输入所述公路转移交通量预测模型,输出预测结果。该方法不仅可以提高公路转移交通量预测的精度,同时具有较好的可解释性,可以直接应用于公路转移交通量预测系统中。


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    Title :

    Road transfer traffic volume prediction method based on discrete selection model


    Additional title:

    一种基于离散选择模型的公路转移交通量预测方法


    Contributors:
    CUI SHU (author) / LI MENG (author) / WANG JIALI (author) / GENG QINGQIAO (author) / LI YING (author) / RAO ZONGHAO (author) / WANG YU (author) / QIU DIXIAN (author) / HUANG QIAN (author) / WANG WANJIN (author)

    Publication date :

    2025-02-18


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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