IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14104-d956865.html
   My bibliography  Save this article

Modified State-Dependent Queuing Model for the Capacity Analysis of Metro Rail Transit Station Corridor during COVID-19

Author

Listed:
  • Afaq Khattak

    (College of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Hamad Almujibah

    (Department of Civil Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Feng Chen

    (College of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Hussain S. Alyami

    (Department of Transportation and Equipment Services, Saudi Aramco, Dhahran 34471, Saudi Arabia)

Abstract

The COVID-19 pandemic policies have had a significant impact on the daily commuter flow at the metro rail transit stations. In this study, we propose a modified state-dependent M ( n )/G( n )/ C / C queuing model for the analysis of commuter flow in the corridor of metro rail transit stations in the COVID-19 situation in order to ensure safe social distance. The proposed model is a finite capacity queuing system with state-dependent commuter arrivals and state-dependent service rates based on the flow–density relationship. First, a mathematical queuing model is developed by using the birth–death process (BDP) and the expected number of commuters, and average area occupied per commuter and blocking probabilities are computed. Then, the accuracy of the proposed model is verified by a discrete-event simulation (DES) framework. (1) The proposed model’s results are compared to those of the existing M /G( n )/ C / C model. The proposed modified model’s sensitivity analysis revealed that the anticipated number of commuters in the corridor remains smaller when the arrival rate is state-dependent. (2) In accordance with COVID-19 protocol, when the facility is congested, commuters are discouraged from entering and a safe social distance is maintained between them. (3) No commuters are impeded, and adequate throughput is ensured from the corridor. The proposed model will assist the metro rail transit station operators in making intelligent decisions regarding the operations in the COVID-19 situation.

Suggested Citation

  • Afaq Khattak & Hamad Almujibah & Feng Chen & Hussain S. Alyami, 2022. "Modified State-Dependent Queuing Model for the Capacity Analysis of Metro Rail Transit Station Corridor during COVID-19," Sustainability, MDPI, vol. 14(21), pages 1-14, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14104-:d:956865
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14104/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/21/14104/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Basu, Rounaq & Ferreira, Joseph, 2021. "Sustainable mobility in auto-dominated Metro Boston: Challenges and opportunities post-COVID-19," Transport Policy, Elsevier, vol. 103(C), pages 197-210.
    2. Naveen, B.R. & Gurtoo, Anjula, 2022. "Public transport strategy and epidemic prevention framework in the Context of Covid-19," Transport Policy, Elsevier, vol. 116(C), pages 165-174.
    3. Yonghwa Park & Seung B. Ahn, 2003. "Optimal assignment for check-in counters based on passenger arrival behaviour at an airport," Transportation Planning and Technology, Taylor & Francis Journals, vol. 26(5), pages 397-416, October.
    4. A. Regattieri & R. Gamberini & F. Lolli & R. Manzini, 2010. "Designing production and service systems using queuing theory: principles and application to an airport passenger security screening system," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 6(2), pages 206-225.
    5. Zhu, Juanxiu & Hu, Lu & Jiang, Yangsheng & Khattak, Afaq, 2017. "Circulation network design for urban rail transit station using a PH(n)/PH(n)/C/C queuing network model," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1043-1068.
    6. Hu, Lu & Jiang, Yangsheng & Zhu, Juanxiu & Chen, Yanru, 2015. "A PH/PH(n)/C/C state-dependent queuing model for metro station corridor width design," European Journal of Operational Research, Elsevier, vol. 240(1), pages 109-126.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khattak, Afaq & Hussain, Arshad, 2021. "Hybrid DES-PSO framework for the design of commuters’ circulation space at multimodal transport interchange," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 180(C), pages 205-229.
    2. Hu, Lu & Zhao, Bin & Zhu, Juanxiu & Jiang, Yangsheng, 2019. "Two time-varying and state-dependent fluid queuing models for traffic circulation systems," European Journal of Operational Research, Elsevier, vol. 275(3), pages 997-1019.
    3. Roman Dostál & Josef Kocourek & Aneta Matysková & Karolína Moudrá & Vojtěch Nižňanský, 2021. "The Implementation of the Smart City Process—Researchers’ Knowledge in Detecting Transport System Defects," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    4. Ballo, Lukas & de Freitas, Lucas Meyer & Meister, Adrian & Axhausen, Kay W., 2023. "The E-Bike City as a radical shift toward zero-emission transport: Sustainable? Equitable? Desirable?," Journal of Transport Geography, Elsevier, vol. 111(C).
    5. de Lange, Robert & Samoilovich, Ilya & van der Rhee, Bo, 2013. "Virtual queuing at airport security lanes," European Journal of Operational Research, Elsevier, vol. 225(1), pages 153-165.
    6. Ying Liu & Xiuqing Yang & Yong Xiang & Yi Chen & Gang Mao & Xinzhi Zhou, 2022. "Allocation and optimization of shared self-service check-in system based on integer programming model," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 532-556, August.
    7. Marta Borowska-Stefańska & Michał Kowalski & Paulina Kurzyk & Alireza Sahebgharani & Szymon Wiśniewski, 2022. "Spatiotemporal Changeability of the Load of the Urban Road Transport System under Permanent and Short-Term Legal and Administrative Retail Restrictions," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    8. Wojciech Kazimierz Szczepanek & Maciej Kruszyna, 2022. "The Impact of COVID-19 on the Choice of Transport Means in Journeys to Work Based on the Selected Example from Poland," Sustainability, MDPI, vol. 14(13), pages 1-9, June.
    9. Zhou, Kaile & Hu, Dingding & Li, Fangyi, 2022. "Impact of COVID-19 on private driving behavior: Evidence from electric vehicle charging data," Transport Policy, Elsevier, vol. 125(C), pages 164-178.
    10. Kayikci, Yasanur & Kabadurmus, Ozgur, 2022. "Barriers to the adoption of the mobility-as-a-service concept: The case of Istanbul, a large emerging metropolis," Transport Policy, Elsevier, vol. 129(C), pages 219-236.
    11. Bagdatli, Muhammed Emin Cihangir & Ipek, Fatima, 2022. "Transport mode preferences of university students in post-COVID-19 pandemic," Transport Policy, Elsevier, vol. 118(C), pages 20-32.
    12. Andres Sevtsuk & Rounaq Basu & Bahij Chancey, 2021. "We shape our buildings, but do they then shape us? A longitudinal analysis of pedestrian flows and development activity in Melbourne," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-23, September.
    13. Ornek, M. Arslan & Ozturk, Cemalettin & Sugut, Ipek, 2019. "Model-based heuristic for counter assignment problem with operational constrains: A case study," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 57-64.
    14. Wang, Chunan & Jiang, Changmin, 2022. "How do pandemics affect intercity air travel? Implications for traffic and environment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 330-353.
    15. Vega-Gonzalo, Maria & Gomez, Juan & Christidis, Panayotis, 2023. "How has COVID-19 changed private car use in European urban areas? An analysis of the effect of socio-economic characteristics and mobility habits," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    16. Shi, Yihan & Xu, Jie & Zhang, Hui & Jia, Limin & Qin, Yong, 2022. "Empirical investigation on turning behavior of passengers in subway station," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    17. Shi, Yihan & Xu, Jie & Zhang, Hui & Jia, Limin & Qin, Yong, 2022. "Walking model on passenger in merging passage of subway station considering overtaking behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    18. Joao Tiago Aparicio & Elisabete Arsenio & Francisco C. Santos & Rui Henriques, 2022. "LINES: muLtImodal traNsportation rEsilience analySis," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    19. Ryan Palmer & Martin Utley, 2020. "On the modelling and performance measurement of service networks with heterogeneous customers," Annals of Operations Research, Springer, vol. 293(1), pages 237-268, October.
    20. Yuko Arai & Yukari Niwa & Takahiko Kusakabe & Kentaro Honma, 2023. "How has the Covid-19 pandemic affected wheelchair users? Time-series analysis of the number of railway passengers in Tokyo," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14104-:d:956865. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.