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Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area

Author

Listed:
  • Sewmini Jayatilake

    (Queensland University of Technology, School of Civil and Environmental Engineering)

  • Jonathan M. Bunker

    (Queensland University of Technology, School of Civil and Environmental Engineering)

  • Ashish Bhaskar

    (Queensland University of Technology, School of Civil and Environmental Engineering)

  • Marc Miska

    (Queensland University of Technology, School of Civil and Environmental Engineering)

Abstract

It is important to evaluate the quality of service (QoS) of bus rapid transit (BRT) station platform operation. Passenger-specific area (PSA) is used as a QoS measure which is determined by considering passenger activities separately. As passengers perform various activities on the same platform space, there is a need to evaluate BRT platform QoS by considering the activities collectively. When evaluating transit station platforms, many researchers calculated PSA for the whole platform area, while very few researchers highlighted the importance of evaluating the platform as small, partitioned areas. By considering these findings and gaps in the literature, this study evaluates QoS of the platform on a cell by cell basis using PSA. We use time–space analysis and passenger-minutes of each activity to develop a methodology to determine PSA, by considering stationary passengers, circulating passengers, and passengers overall. To evaluate platform QoS, we define threshold service levels using passenger-minutes of activities and Fruin’s QoS criteria. For the case study BRT station, we find that PSA varies significantly between platform cells. It is evident from the results that it is important to identify highly congested areas in the platform and apply measures to improve platform QoS.

Suggested Citation

  • Sewmini Jayatilake & Jonathan M. Bunker & Ashish Bhaskar & Marc Miska, 2021. "Time–space analysis to evaluate cell-based quality of service in bus rapid transit station platforms through passenger-specific area," Public Transport, Springer, vol. 13(2), pages 395-427, June.
  • Handle: RePEc:spr:pubtra:v:13:y:2021:i:2:d:10.1007_s12469-021-00267-z
    DOI: 10.1007/s12469-021-00267-z
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    References listed on IDEAS

    as
    1. Jonathan M. Bunker, 2018. "High volume bus stop upstream average waiting time for working capacity and quality of service," Public Transport, Springer, vol. 10(2), pages 311-333, August.
    2. Md Rokibul Islam & Md Hadiuzzaman & Rajib Banik & Md Mehedi Hasnat & Sarder Rafee Musabbir & Sanjana Hossain, 2016. "Bus service quality prediction and attribute ranking: a neural network approach," Public Transport, Springer, vol. 8(2), pages 295-313, September.
    3. Sebastian Seriani & Taku Fujiyama & Catherine Holloway, 2017. "Exploring the pedestrian level of interaction on platform conflict areas at metro stations by real-scale laboratory experiments," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(1), pages 100-118, January.
    4. Hänseler, Flurin S. & Bierlaire, Michel & Scarinci, Riccardo, 2016. "Assessing the usage and level-of-service of pedestrian facilities in train stations: A Swiss case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 106-123.
    5. Lam, William H. K. & Cheung, Chung-Yu & Lam, C. F., 1999. "A study of crowding effects at the Hong Kong light rail transit stations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(5), pages 401-415, June.
    6. Bo Yang & Xuedong Yan & Dahai Guo, 2015. "Level of Service Analysis Based on Maximum Number of Passengers in Waiting Room of Railway Passenger Station Using Arena Simulation," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-14, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Bus rapid transit; Station platforms; Platform cell; Time–space analysis; Passenger-specific area; Quality of service; Service levels;
    All these keywords.

    JEL classification:

    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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