The invention relates to a deep learning bus arrival time prediction method based on spatial-temporal characteristics, which is realized by a bus data collection system, and comprises the following steps: S1, taking stations of a bus line in an operation area and inter-station road sections as nodes to obtain an undirected graph; s2, collecting GPS data, and calculating driving time and arrival stop time; s3, calculating time features by using a statistical method, and obtaining spatial features from map information; s4, splicing the time features and the space features to obtain complete feature data; s5, sorting the complete feature data, and combining the complete feature data with the undirected graph to form a set as input; s6, establishing and training a regional bus arrival time prediction model; and S7, calculating a regional bus arrival time prediction value. According to the method, the bus arrival time prediction of multiple lines in the area can be realized, the time prediction of a certain station in the area reaching any other station in the area can be realized, and the operation efficiency of the bus and the travel experience of passengers are effectively improved.

    本发明涉及基于时空特征的深度学习公交车到站时间预测方法,由公交数据收集系统实现,包括以下步骤:S1:将运营区域中公交线路的站点以及站间路段为节点,得到一个无向图;S2:采集GPS数据,计算行驶时间以及到站停靠时间;S3:利用统计学方法计算时间特征,并从地图信息中获取空间特征;S4:将时间特征和空间特征进行拼接,得到完整特征数据;S5:对完整特征数据进行排序,并与无向图组合成集合,作为输入;S6:建立并训练区域公交车到站时间预测模型;S7:计算区域公交车到站时间预测值。本发明方法能够实现区域内多条线路的公交到站时间预测能够实现区域内某站点到达区域内其他任意站点的时间预测,有效提高公交车的运营效率和乘客出行体验。


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    Titel :

    Deep learning bus arrival time prediction method based on spatial-temporal characteristics


    Weitere Titelangaben:

    基于时空特征的深度学习公交车到站时间预测方法


    Beteiligte:
    LI YI (Autor:in) / CHEN BAILIN (Autor:in) / YANG WENQIANG (Autor:in) / WU WENYUAN (Autor:in)

    Erscheinungsdatum :

    23.05.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    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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