Estimation of link travel time correlation of a bus route is essential to many bus operation applications. Link travel time on a bus route could exhibit complex correlation structures, such as long-range correlations, negative correlations, and time-varying correlations. This paper develops a Bayesian Gaussian model to estimate the link travel time correlation matrix of a bus route using smart-card-like data. Our method overcomes the small-sample-size problem in correlation matrix estimation by borrowing/integrating those incomplete observations from other bus routes. We first conduct a synthetic experiment and results show that the proposed method produces an accurate estimation for correlations with credible intervals. Next, we perform experiments on a real-world bus route with in-out-stop record data; results show that both local and long-range correlations exist on this bus route. Finally, we demonstrate an application of using the estimated covariance matrix to make probabilistic forecasting of link and trip travel time.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Bayesian inference for link travel time correlation of a bus route


    Weitere Titelangaben:

    TRANSPORTMETRICA B
    X. CHEN ET AL.


    Beteiligte:
    Chen, Xiaoxu (Autor:in) / Cheng, Zhanhong (Autor:in) / Sun, Lijun (Autor:in)


    Erscheinungsdatum :

    31.12.2024


    Format / Umfang :

    28 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    TRAVEL ROUTE LINK GENERATION DEVICE AND TRAVEL ROUTE LINK GENERATION METHOD

    SUZUKI ATSUYUKI | Europäisches Patentamt | 2020

    Freier Zugriff

    Estimating Travel Time Distributions by Bayesian Network Inference

    Prokhorchuk, Anatolii / Dauwels, Justin / Jaillet, Patrick | IEEE | 2020


    Link travel time prediction for decentralized route guidance architectures

    Wunderlich, K.E. / Kaufman, D.E. / Smith, R.L. | IEEE | 2000


    Link Travel Time Prediction for Decentralized Route Guidance Architectures

    Wunderlich, K. E. / Kaufman, D. E. / Smith, R. L. | British Library Online Contents | 2000


    Neighbouring link travel time inference method using artificial neural network

    Vu, Luong H. / Passow, Benjamin N. / Paluszczyszyn, Daniel et al. | IEEE | 2017