IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v126y2019icp67-82.html
   My bibliography  Save this article

A link criticality index embedded in the convex combinations solution of user equilibrium traffic assignment

Author

Listed:
  • Almotahari, Amirmasoud
  • Yazici, M. Anil

Abstract

Identification of critical components in transportation networks is an essential part of designing robust and resilient systems. Topological criticality measures are based on graph theory and are applicable in multiple domains including communication and socialnetworks. However, the non-linearity of link performance functions in transportation systems does not allow a perfect domain transfer of topological measures. Hence, transportation researchers take traffic flow characteristics into account while developing criticality measures. In such approaches, typically, a network performance measure is selected, then links are removed one-by-one, and traffic demand is reassigned to the updated network to calculate the impacts of each link failure. This consecutive link removal procedure requires multiple assignments which create a computational burden, especially for large networks. Overall objectives of this paper are (1) to compare and contrast selected criticality measures, and (2) to develop a new measure to identify critical components of transportation network, considering both traffic characteristics and network topology. For this purpose, the user equilibrium traffic assignment formulation is utilized, and the convex combinations solution algorithm is exploited for identification of link criticality ranking within a single traffic assignment. The developed measure is named Link Criticality Index (LCI). The LCI is compared with the existing measures in the literature through three numerical examples. Pros and cons of the LCI and selected measures are discussed in detail. The results indicate the proposed link criticality measure provides a balanced ranking with respect to connectivity/redundancy as well as the traffic conditions in the network.

Suggested Citation

  • Almotahari, Amirmasoud & Yazici, M. Anil, 2019. "A link criticality index embedded in the convex combinations solution of user equilibrium traffic assignment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 67-82.
  • Handle: RePEc:eee:transa:v:126:y:2019:i:c:p:67-82
    DOI: 10.1016/j.tra.2019.06.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856418315672
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2019.06.005?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. Knoop, Victor L. & Snelder, Maaike & van Zuylen, Henk J. & Hoogendoorn, Serge P., 2012. "Link-level vulnerability indicators for real-world networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 843-854.
    2. Federico Rupi & Silvia Bernardi & Guido Rossi & Antonio Danesi, 2015. "The Evaluation of Road Network Vulnerability in Mountainous Areas: A Case Study," Networks and Spatial Economics, Springer, vol. 15(2), pages 397-411, June.
    3. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    4. Karen E Joyce & Paul J Laurienti & Jonathan H Burdette & Satoru Hayasaka, 2010. "A New Measure of Centrality for Brain Networks," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-13, August.
    5. Chen, Bi Yu & Lam, William H.K. & Sumalee, Agachai & Li, Qingquan & Li, Zhi-Chun, 2012. "Vulnerability analysis for large-scale and congested road networks with demand uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 501-516.
    6. Oded Cats & Erik Jenelius, 2014. "Dynamic Vulnerability Analysis of Public Transport Networks: Mitigation Effects of Real-Time Information," Networks and Spatial Economics, Springer, vol. 14(3), pages 435-463, December.
    7. Demirel, Hande & Kompil, Mert & Nemry, Françoise, 2015. "A framework to analyze the vulnerability of European road networks due to Sea-Level Rise (SLR) and sea storm surges," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 62-76.
    8. Reggiani, Aura & Nijkamp, Peter & Lanzi, Diego, 2015. "Transport resilience and vulnerability: The role of connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 4-15.
    9. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    10. Watling, David & Balijepalli, N.C., 2012. "A method to assess demand growth vulnerability of travel times on road network links," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 772-789.
    11. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    12. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.
    13. Sullivan, J.L. & Novak, D.C. & Aultman-Hall, L. & Scott, D.M., 2010. "Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 323-336, June.
    14. Voltes-Dorta, Augusto & Rodríguez-Déniz, Héctor & Suau-Sanchez, Pere, 2017. "Vulnerability of the European air transport network to major airport closures from the perspective of passenger delays: Ranking the most critical airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 119-145.
    15. Taylor, Michael A.P. & Susilawati,, 2012. "Remoteness and accessibility in the vulnerability analysis of regional road networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 761-771.
    16. Cats, O. & Yap, M. & van Oort, N., 2016. "Exposing the role of exposure: Public transport network risk analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 1-14.
    17. Cats, Oded & Koppenol, Gert-Jaap & Warnier, Martijn, 2017. "Robustness assessment of link capacity reduction for complex networks: Application for public transport systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 544-553.
    18. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
    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. Fan, Bing & Tan, Hongtao & Li, Yaqun, 2023. "Critical link identification algorithm for power communication networks in SDN architecture," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    2. Zhang, Jianhua & Shao, Wenchao & Yang, Liqiang & Zhao, Xun & Liu, Weizhi, 2023. "Robustness assessments of urban rail transit networks based on user equilibrium with time compensation mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).
    3. Almotahari, Amirmasoud & Yazici, Anil, 2021. "A computationally efficient metric for identification of critical links in large transportation networks," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    4. Navin Bhatta & Shakhawat H. Tanim & Pamela Murray-Tuite, 2024. "Dynamics of Link Importance through Normal Conditions, Flood Response, and Recovery," Sustainability, MDPI, vol. 16(2), pages 1-35, January.
    5. Kurmankhojayev, Daniyar & Li, Guoyuan & Chen, Anthony, 2024. "Link criticality index: Refinement, framework extension, and a case study," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    6. Mylonas, Chrysostomos & Mitsakis, Evangelos & Kepaptsoglou, Konstantinos, 2023. "Criticality analysis in road networks with graph-theoretic measures, traffic assignment, and simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).

    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. Almotahari, Amirmasoud & Yazici, Anil, 2021. "A computationally efficient metric for identification of critical links in large transportation networks," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    3. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Gonçalves, L.A.P.J. & Ribeiro, P.J.G., 2020. "Resilience of urban transportation systems. Concept, characteristics, and methods," Journal of Transport Geography, Elsevier, vol. 85(C).
    5. Caterina Malandri & Luca Mantecchini & Filippo Paganelli & Maria Nadia Postorino, 2021. "Public Transport Network Vulnerability and Delay Distribution among Travelers," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    6. Reggiani, Aura & Nijkamp, Peter & Lanzi, Diego, 2015. "Transport resilience and vulnerability: The role of connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 4-15.
    7. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    8. Ghavami, Seyed Morsal, 2019. "Multi-criteria spatial decision support system for identifying strategic roads in disaster situations," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 23-36.
    9. Oliveira, Eduardo Leal de & Portugal, Licínio da Silva & Porto Junior, Walter, 2016. "Indicators of reliability and vulnerability: Similarities and differences in ranking links of a complex road system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 195-208.
    10. Muriel-Villegas, Juan E. & Alvarez-Uribe, Karla C. & Patiño-Rodríguez, Carmen E. & Villegas, Juan G., 2016. "Analysis of transportation networks subject to natural hazards – Insights from a Colombian case," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 151-165.
    11. Khademi, Navid & Babaei, Mohsen & Schmöcker, Jan-Dirk & Fani, Amirhossein, 2018. "Analysis of incident costs in a vulnerable sparse rail network – Description and Iran case study," Research in Transportation Economics, Elsevier, vol. 70(C), pages 9-27.
    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. Qing-Chang Lu & Shan Lin, 2019. "Vulnerability Analysis of Urban Rail Transit Network within Multi-Modal Public Transport Networks," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
    14. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    15. Mylonas, Chrysostomos & Mitsakis, Evangelos & Kepaptsoglou, Konstantinos, 2023. "Criticality analysis in road networks with graph-theoretic measures, traffic assignment, and simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    16. 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.
    17. Pan, Shouzheng & Ling, Shuai & Jia, Ning & Liu, Yiliu & He, Zhengbing, 2024. "On the dynamic vulnerability of an urban rail transit system and the impact of human mobility," Journal of Transport Geography, Elsevier, vol. 116(C).
    18. Victor Cantillo & Luis F. Macea & Miguel Jaller, 2019. "Assessing Vulnerability of Transportation Networks for Disaster Response Operations," Networks and Spatial Economics, Springer, vol. 19(1), pages 243-273, March.
    19. Cats, Oded & Koppenol, Gert-Jaap & Warnier, Martijn, 2017. "Robustness assessment of link capacity reduction for complex networks: Application for public transport systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 544-553.
    20. 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.

    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:eee:transa:v:126:y:2019:i:c:p:67-82. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.