The invention discloses an urban area road network traffic flow prediction method and system based on a hybrid deep learning model, and the method comprises the steps: carrying out traffic flow statistics based on vehicle passing data of a checkpoint; performing spatial-temporal distribution characteristic analysis on the traffic flow data of the checkpoint, and performing characteristic extraction according to an analysis result to obtain spatial-temporal influence factors; according to the space-time influence factors, constructing and training a ConvLSTM and BiLSTM mixed deep learning model; performing synchronous prediction on the traffic flow of an urban regional road network, selecting a prediction loss function and an evaluation index, and performing visual expression on a result; calculating the traffic flow change degree through a linear time sequence prediction model Prophet, carrying out traffic state recognition, and achieving traffic state pre-judgment. According to the invention, a traffic management department can be helped to carry out dynamic management scheduling on urban roads, optimization management is carried out on an urban road network from the overall situation, a management strategy and a management scheme are formulated, and effective data support is provided for traffic managers and decision makers.

    本发明公开了一种基于混合深度学习模型的城市区域路网过车流量预测方法及其系统,包括:基于卡口过车数据,进行交通流量统计;对卡口过车流量数据进行时空分布特征分析,并且根据分析结果进行特征提取,获取到时空影响因子;根据时空影响因子,构建和训练ConvLSTM与BiLSTM混合深度学习模型;对城市区域路网交通流量进行同步预测,选取预测损失函数与评价指标,并对结果进行可视化表达;通过线性时间序列预测模型Prophet计算交通流量变化度,进行交通状态识别,实现交通状态预判。本发明能够帮助交通管理部门对城市道路进行动态管理调度,从全局出发对城市路网进行优化管理,制定管理策略与管理方案,为交通管理者和决策者提供有效的数据支撑。


    Access

    Download


    Export, share and cite



    Title :

    Urban area road network traffic flow prediction method and system based on mixed deep learning model


    Additional title:

    基于混合深度学习模型的城市区域路网过车流量预测方法及其系统


    Contributors:
    ZHANG HONG (author) / XU XIN (author) / GUO FEI (author) / WANG HUANDONG (author)

    Publication date :

    2021-08-27


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    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 / 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



    Urban road traffic flow prediction method and device based on space-time deep learning model

    JIA TAO / YAN PENGGAO | European Patent Office | 2020

    Free access

    Urban road traffic state prediction system based on deep learning

    HAO WEI / YI KEFU / GAO ZHIBO et al. | European Patent Office | 2020

    Free access

    Urban traffic road network traffic flow prediction method considering carbon emission model

    LI RUI / HU YUEGUI / YANG ZHIJIA et al. | European Patent Office | 2024

    Free access

    Traffic flow prediction method and system for urban road network

    LI SONGJIANG / WU NING / WANG PENG | European Patent Office | 2021

    Free access

    Urban high-density road network mixed traffic flow cellular transmission simulation prediction method

    XU CHENGCHENG / WANG ZHIHAO / PENG CHANG et al. | European Patent Office | 2023

    Free access