Public transportation plays an important role in enhancing the environmental sustainability of urban traffic system. Since the 1980s, public transport prioritization at signalized intersections has been instrumental in reducing travel time and improving passenger comfort. The development of V2X (Vehicle-to-Everything) technology presents new opportunities to further enhance the prioritization. Accurate travel time prediction is crucial for optimizing public transport prioritization at intersections. In this study, we introduce a set of models for the prediction of travel time and apply them to a real-world dataset. Then the applicability of our models is compared by analyzing the temporal and spatial characteristics of the accuracy and their temporal consistency of predictions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Comparison of Models for the Prediction of Travel Time for Public Transport Prioritization


    Contributors:


    Publication date :

    2024-02-26


    Size :

    714664 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Public transport prioritization

    Europäische Kommission, Generaldirektion Verkehr / Università degli studi di Roma "La Sapienza", Dipartimento di idraulica, trasporti e strade | TIBKAT | 1996


    Public transport prioritization

    Europäische Kommission, Generaldirektion Verkehr | SLUB | 1996


    Prediction system for public transport travel time using big data

    LEE HYEON SOO / YANG JUN MO / LEE JIN WOO et al. | European Patent Office | 2018

    Free access

    / Prediction system for public transport travel time using big data

    LEE HYEON SOO / YANG JUN MO / LEE JIN WOO et al. | European Patent Office | 2018

    Free access

    Public Transport Prioritization in Consideration of Congestions

    Hepner, Eduard / Duensing, Josua / Zhao, Chao et al. | Springer Verlag | 2023