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Factorial Design with Simulation for the Optimization of the Level of Service in the Platform-Train Interface of Metro Stations—A Pilot Study

Author

Listed:
  • Matias Kulczewski

    (Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Santiago de Chile 7620001, Chile)

  • Andres Wilson

    (Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Santiago de Chile 7620001, Chile)

  • Sebastian Seriani

    (Escuela de Ingeniería de Construcción y Transporte, Pontifica Universidad Católica de Valparaíso, Valparaíso 2362804, Chile)

  • Taku Fujiyama

    (Faculty of Civil, Environmental and Geomatic Engineering, University College London, Chadwick Building, Gower St., London WC1E 6BT, UK)

Abstract

Metro stations are considered complex areas of pedestrian mobility due to the increasing congestion, due to the a high level of demand of different circulation spaces. Given this situation and the limited physical spaces remaining to develop transport systems in urban areas, railways acquire greater relevance given the need to mobilize pedestrians. Within the stations, the most problematic area is the platform-train interface (PTI) due to the high number of interactions between passengers boarding and alighting. The objective of this study is to identify the PTI configuration that maximizes the level of service for passengers, safeguards the operational continuity of the system and improves user experience by reducing dissatisfaction and delay times. For this, a pedestrian microsimulation model is used in order to recreate the reality of a generic metro station and its different scenarios given the combinations of two factors: the platform configurations (topology) and the traffic control elements. Subsequently, these scenarios are analyzed through a factorial design, looking for the situation that optimizes the combination of metrics chosen in a weighted way. Finally, it is found that the PTI configuration that maximizes the level of service for users is the mixed station with signaling. It is this which includes the factors with the greatest positive effect on the chosen metrics.

Suggested Citation

  • Matias Kulczewski & Andres Wilson & Sebastian Seriani & Taku Fujiyama, 2022. "Factorial Design with Simulation for the Optimization of the Level of Service in the Platform-Train Interface of Metro Stations—A Pilot Study," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15840-:d:986776
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    References listed on IDEAS

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    1. Xenia Karekla & Nick Tyler, 2012. "Reduced dwell times resulting from train--platform improvements: the costs and benefits of improving passenger accessibility to metro trains," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(5), pages 525-543, January.
    2. Fernández, Rodrigo & Valencia, Alejandra & Seriani, Sebastian, 2015. "On passenger saturation flow in public transport doors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 102-112.
    3. Sebastian Seriani & Vicente Aprigliano Fernandes & Paola Moraga & Fabian Cortes, 2022. "Experimental Location of the Vertical Handrail to Improve the Accessibility of Wheelchair Passengers Boarding and Alighting at Metro Stations—A Pilot Study," Sustainability, MDPI, vol. 14(15), pages 1-22, July.
    4. 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.
    5. Guo, Ren-Yong & Wong, S.C. & Huang, Hai-Jun & Zhang, Peng & Lam, William H.K., 2010. "A microscopic pedestrian-simulation model and its application to intersecting flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 515-526.
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