IDEAS home Printed from https://ideas.repec.org/a/spr/pubtra/v9y2017i1d10.1007_s12469-017-0158-y.html
   My bibliography  Save this article

Enabling large-scale transit microsimulation for disruption response support using the Nexus platform

Author

Listed:
  • Siva Srikukenthiran

    (University of Toronto)

  • Amer Shalaby

    (University of Toronto)

Abstract

In many large cities, public transit systems have been carrying an ever-increasing burden of commuters. In such systems, service disruptions can negatively impact system performance and transit users well after they are resolved. Currently, transit agencies handle these disruption episodes in an ad-hoc fashion, largely due to the lack of adequate analytical tools to aid in analyzing and selecting appropriate response strategies. This paper presents a proof-of-concept case study of the Greater Toronto transit network using Nexus, a new crowd dynamics and transit network simulation platform. Nexus enables detailed simulation of all transit system actors using a novel method of linking together established simulators of surface transit, fully separated rail transit, and stations. Transit users, as agents in the model, move between the different simulators and have their routes determined by an external dynamic routing module. The case study focuses on interfacing Nexus with a commercial pedestrian simulator, MassMotion, to allow for detailed crowd simulation at key stations, and illustrating how the platform could be used for disruption management. To this end, the impact of disruptions of various lengths was analyzed, and a simple response strategy was implemented to provide an example of how the system could be used to test mitigating strategies.

Suggested Citation

  • Siva Srikukenthiran & Amer Shalaby, 2017. "Enabling large-scale transit microsimulation for disruption response support using the Nexus platform," Public Transport, Springer, vol. 9(1), pages 411-435, July.
    • Handle: RePEc:spr:pubtra:v:9:y:2017:i:1:d:10.1007_s12469-017-0158-y
    DOI: 10.1007/s12469-017-0158-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12469-017-0158-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12469-017-0158-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lee, Keumsook & Jung, Woo-Sung & Park, Jong Soo & Choi, M.Y., 2008. "Statistical analysis of the Metropolitan Seoul Subway System: Network structure and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6231-6234.
    2. Angeloudis, Panagiotis & Fisk, David, 2006. "Large subway systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 553-558.
    3. Mohamed Wahba & Amer Shalaby, 2011. "Large-scale application of MILATRAS: case study of the Toronto transit network," Transportation, Springer, vol. 38(6), pages 889-908, November.
    4. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mahmood Mahmoodi Nesheli & Siva Srikukenthiran & Amer Shalaby, 2022. "An optimization model for planning limited-stop transit operations," Public Transport, Springer, vol. 14(1), pages 63-83, March.
    2. Aya Aboudina & Alaa Itani & Ehab Diab & Siva Srikukenthiran & Amer Shalaby, 2021. "Evaluation of bus bridging scenarios for railway service disruption management: a users’ delay modelling tool," Public Transport, Springer, vol. 13(3), pages 457-481, October.
    3. 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.

    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. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    2. Cats, Oded, 2017. "Topological evolution of a metropolitan rail transport network: The case of Stockholm," Journal of Transport Geography, Elsevier, vol. 62(C), pages 172-183.
    3. Yi Shen & Gang Ren & Bin Ran, 2021. "Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China," Transportation, Springer, vol. 48(2), pages 537-553, April.
    4. Yingying Xing & Jian Lu & Shendi Chen, 2016. "Weighted Complex Network Analysis of Shanghai Rail Transit System," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-8, August.
    5. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    6. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    7. Zhang, Yanjie & Ayyub, Bilal M. & Saadat, Yalda & Zhang, Dongming & Huang, Hongwei, 2020. "A double-weighted vulnerability assessment model for metrorail transit networks and its application in Shanghai metro," International Journal of Critical Infrastructure Protection, Elsevier, vol. 29(C).
    8. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    9. Zhang, Jianhua & Wang, Shuliang & Zhang, Zhaojun & Zou, Kuansheng & Shu, Zhan, 2016. "Characteristics on hub networks of urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 502-507.
    10. Yang, Zhijie & Chen, Xiaolong, 2018. "Evolution assessment of Shanghai Urban Rail Transit Network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1263-1274.
    11. Hui Xu & Liudan Jiao & Shulin Chen & Milan Deng & Ningxin Shen, 2018. "An Innovative Approach to Determining High-Risk Nodes in a Complex Urban Rail Transit Station: A Perspective of Promoting Urban Sustainability," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    12. Lu, Qing-Chang, 2018. "Modeling network resilience of rail transit under operational incidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 227-237.
    13. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    14. Zhang, Jianhua & Song, Bo & Zhang, Zhaojun & Liu, Haikuan, 2014. "An approach for modeling vulnerability of the network of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 127-136.
    15. Zhang, Jianhua & Xu, Xiaoming & Hong, Liu & Wang, Shuliang & Fei, Qi, 2011. "Networked analysis of the Shanghai subway network, in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4562-4570.
    16. Feng, Jia & Li, Xiamiao & Mao, Baohua & Xu, Qi & Bai, Yun, 2017. "Weighted complex network analysis of the Beijing subway system: Train and passenger flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 213-223.
    17. Wang, Zhiru & Niu, Fangyan & Yang, Lili & Su, Guofeng, 2020. "Modeling a subway network: A hot-point attraction-driven evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    18. Xianing Wang & Zhan Zhang & Ying Wang & Jun Yang & Linjun Lu, 2022. "A Study on Safety Evaluation of Pedestrian Flows Based on Partial Impact Dynamics by Real-Time Data in Subway Stations," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    19. Paulsen, Mads & Rasmussen, Thomas Kjær & Nielsen, Otto Anker, 2021. "Impacts of real-time information levels in public transport: A large-scale case study using an adaptive passenger path choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 155-182.
    20. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).

    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:spr:pubtra:v:9:y:2017:i:1:d:10.1007_s12469-017-0158-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.