A system uses machine models to estimate trip durations or distance. The system trains a historical model to estimate trip duration using characteristics of past trips. The system trains a real-time model to estimate trip duration using characteristics of recently completed trips. The historical and real-time models may use different time windows of training data to predict estimates, and may be trained to predict an adjustment to an initial trip estimate. A selector model is trained to predict whether the historical model, the real-time model, or a combination of the historical and real-time models will more accurately estimate a trip duration, given features associated with a trip duration request, and the system accordingly uses the models to estimate a trip duration. In some embodiments, the real-time model and the selector may be trained using batch machine learning techniques which allow the models to incorporate new trip data as trips complete.


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    Titel :

    Generation of trip estimates using real-time data and historical data


    Beteiligte:
    YAO SHIJING (Autor:in) / CAI XIAO (Autor:in)

    Erscheinungsdatum :

    2020-10-27


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G01C Messen von Entfernungen, Höhen, Neigungen oder Richtungen , MEASURING DISTANCES, LEVELS OR BEARINGS / 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



    Generation of trip estimates using real-time data and historical data

    YAO SHIJING / CAI XIAO | Europäisches Patentamt | 2020

    Freier Zugriff

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    Herrera, Nelida / Smith, Todd / Parr, Scott A. et al. | Transportation Research Record | 2019



    Call for Trip Generation Data

    Online Contents | 1996


    Count Data Models for Trip Generation

    Jang, T. Y. | British Library Online Contents | 2005