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    Influence of travel time variability on train station choice for park-and-rider users

    Access Status
    Open access via publisher
    Authors
    Chen, C.
    Xia, Jianhong (Cecilia)
    Smith, B.
    Olaru, D.
    Taplin, J.
    Han, R.
    Date
    2017
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Chen, C. and Xia, J.(. and Smith, B. and Olaru, D. and Taplin, J. and Han, R. 2017. Influence of travel time variability on train station choice for park-and-rider users, pp. 2477-2493.
    Source Title
    Transportation Research Procedia
    DOI
    10.1016/j.trpro.2017.05.274
    ISSN
    2352-1457
    School
    Department of Spatial Sciences
    URI
    http://hdl.handle.net/20.500.11937/56003
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 The Authors. Published by Elsevier B.V. It is increasingly recognised that park and ride (PnR) is an efficient travel mode joining private car with public transport system for providing low carbon emissions and better social equity. Departure train stations, as a transfer point of the travel mode, are paid more attention by commuters. This paper presents non-linear multinomial logit station choice models for understanding train station choice under travel time unreliability. A research framework about station choice under uncertainty is established based on discrete choice theory, cumulative prospect theory and mean-variance approach. Four weighting functions were tested for the station choice model. The data used to capture PnR users' choice behaviour under uncertainty was collected based on a stated preference experiment designed for D-efficiency and the travel time to the station was obtained from revealed preference data. The results showed that the non-linear MNL model with GE risky weighting function fits the data best. From the model, the respondents' attitude towards travel time variability was identified as risk averse. In addition, PnR users who have experienced greater travel time variations could tend to be more risk averse towards their station choice under travel time variability than those who have experienced less travel time variations.

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