A significant proportion of bus travel time is contributed by dwell time for passenger boarding and alighting. More accurate estimation of bus dwell time (BDT) can enhance efficiency and reliability of public transportation system. Regression and probabilistic models are commonly used in literatures where a set of independent variables are used to define the statistical relationship between BDT and its contributing factors. However, due to technical and monetary constraints, it is not always feasible to collect all the data required for the models to work. More importantly, the contributing factors may vary from one bus route to another. Time series based methods can be of great interest as they require only historical time series data, which can be collected using a facility known as automatic vehicle location (AVL) system. This paper assesses four different time series based methods namely random walk, exponential smoothing, moving average (MA), and autoregressive integrated moving average to model and estimate BDT based on AVL data collected from Auckland. The performances of the proposed methods are ranked based on three important factors namely prediction accuracy, simplicity, and robustness. The models showed promising results and performed differently for central business district (CBD) and non‐CBD bus stops. For CBD bus stops, MA model performed the best, whereas for non‐CBD bus stops, ARIMA model performed the best compared with other time series based models. Copyright © 2014 John Wiley & Sons, Ltd.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Estimation of bus dwell time using univariate time series models




    Publication date :

    2015




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.21 Kraftfahrzeuge / 55.21
    Local classification TIB:    275/7020



    Highway Traffic Parameters Estimation by Using Cell Dwell Time

    Wang, H. / Han, Y. / Liang, Z. | ASCE | 2009


    Highway Traffic Parameters Estimation by Using Cell Dwell Time

    Wang, H. / Han, Y. / Liang, Z. | British Library Conference Proceedings | 2009


    Short-Term Passenger Demand Forecasting Using Univariate Time Series Theory

    Ondrej Cyprich / Vladimír Konečný / Katarína Kiliánová | DOAJ | 2013

    Free access

    Regression-based models for bus dwell time

    Jiang, Xinkai / Yang, Xiaoguang | IEEE | 2014


    Train Dwell Time Models for Rail Passenger Service

    San Hor Peay / Mohd Masirin Mohd Idrus | DOAJ | 2016

    Free access