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Effect of information contagion during train service disruption for an integrated rail-bus transit system

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  • Wen Hua

    (National University of Singapore)

  • Ghim Ping Ong

    (National University of Singapore)

Abstract

Disruption in urban rail services can severely affect passengers’ daily travel activities. Transit agencies and operators, besides providing reliable urban transit services and maintaining rail infrastructures, are also interested in developing effective and efficient disruption management strategies. This paper investigates the effect of information provision and contagion under train service disruption for typical disruption management strategies adopted by transit operators. A dynamic modelling framework is proposed for flow assignment within an integrated rail-bus transit network. Information-based user equilibrium, time-dependent line station waiting time estimation, and dynamic optimal travel path generation are integrated into the network loading procedure. A case study based on the Singapore public transit network is presented. Passenger evolution at selected bus stops around the disrupted train stations, the average time loss and the behavior of mode switch are analyzed under different levels of passenger information awareness. The computational results show the influence of information penetration rate and spread speed on the network performance and demonstrate the crucial role of information awareness in passengers’ travel behaviors during disruption. It also shows that our proposed methodology can comprehensively model the train service disruption in terms of the passenger behaviors, the disruption information contagion mechanism and the disruption effects, which support the public transit agencies to evaluate the system performance based on different information provision plans in order to enhance the disruption management.

Suggested Citation

  • Wen Hua & Ghim Ping Ong, 2018. "Effect of information contagion during train service disruption for an integrated rail-bus transit system," Public Transport, Springer, vol. 10(3), pages 571-594, December.
    • Handle: RePEc:spr:pubtra:v:10:y:2018:i:3:d:10.1007_s12469-018-0192-4
    DOI: 10.1007/s12469-018-0192-4
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    3. Åse Jevinger & Jan A. Persson, 2019. "Exploring the potential of using real-time traveler data in public transport disturbance management," Public Transport, Springer, vol. 11(2), pages 413-441, August.

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