The invention provides an expressway traffic distribution method and system based on a neural network. According to the method, a traffic distribution OD matrix is extracted by using vehicle toll collection information detected by an ETC portal of a highway network in a year and a path information database, and a deep learning model based on a deep neural network containing graph attention is constructed in combination with population data, economic development data and travel impedance data of a district-county-level traffic zone, so that the traffic distribution of the district-county-level traffic zone is obtained. And inputting the data into the model for training so as to optimize parameters of the gravity model and obtain a reasonable gravity model. And finally, realizing an expressway path selection model in combination with an XGBoost algorithm, and dividing traffic flow into a road network. According to the method, fusion of multi-source data, the deep neural network and a machine learning algorithm is realized, the precision of generation, prediction and distribution of the traffic distribution flow is greatly improved, and powerful support is provided for long-term planning management of the expressway.

    本发明提供了一种基于神经网络的高速公路交通分配方法及系统。本发明利用高速公路网的ETC门架在一年内检测到的车辆收费信息以及路径信息数据库,提取了交通分布OD矩阵,结合区县级别交通小区的人口数据、经济发展数据及出行阻抗数据,通过构建基于包含图注意力深度神经网络的深度学习模型,将上述数据输入到模型中进行训练,用以优化重力模型的参数,得到合理的重力模型。最后结合XGBoost算法实现高速公路路径选择模型,将交通流量划分到路网中。本发明实现多源数据、深度神经网络以及机器学习算法的融合,极大提高交通分布流的生成、预测以及分配的精度,为高速公路长期规划管理提供有力支撑。


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    Title :

    Expressway traffic distribution method and system based on neural network


    Additional title:

    一种基于神经网络的高速公路交通分配方法及系统


    Contributors:
    ZHANG JING (author) / BAO QIANHAN (author) / GAO XI (author) / XU AIJUN (author)

    Publication date :

    2024-12-20


    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



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