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Identifying the critical road combination in urban roads network under multiple disruption scenarios

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  • Jin, Kun
  • Wang, Wei
  • Li, Xinran
  • Hua, Xuedong
  • Chen, Siyuan
  • Qin, Shaoyang

Abstract

The promising approach to ensure the robustness of the road network is to identify the critical roads. Previous researches mainly focus on the identification of single critical road. Nevertheless, the impact of one road seems to be limited, and the more practical problem is to figure out the critical road combination wherein multiple roads failures may lead to the serious collapse of a road network. This paper develops a rigorous, extensible, mathematical model to identify the critical combination of roads in urban road networks for multiple disruption scenarios. Specifically, we propose a bi-level mixed-integer nonlinear problem (MINLP) model, which is challenging to solve due to its NP-hard characters. Then the transformation and linearization of constraints help simplify the formula into a single-level mixed-integer linear problem (MILP) formula. Finally, the Nguyen and Sioux Falls networks are sufficiently tested under multiple scenarios with different levels of disruption rate and travel demand. The results confirmed the validity and superiority of the proposed model. From the numerical results, it is more practical to measure the robustness of the road network than topological analysis. Besides, the most critical combination with multiple-link failures is not simply the combination of most critical roads with single-link failure, and these roads are not necessarily connected or in the neighborhood of each other. The results also correctly evaluate the impact of disconnection, which could provide advice for managers with preferences for accessibility and travel time.

Suggested Citation

  • Jin, Kun & Wang, Wei & Li, Xinran & Hua, Xuedong & Chen, Siyuan & Qin, Shaoyang, 2022. "Identifying the critical road combination in urban roads network under multiple disruption scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    • Handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007506
    DOI: 10.1016/j.physa.2022.128192
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    References listed on IDEAS

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    1. Yaoming Zhou & Jiuh‐Biing Sheu & Junwei Wang, 2017. "Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1477-1494, August.
    2. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    3. Akbarzadeh, Meisam & Salehi Reihani, Sayed Farzin & Samani, Keivan Aghababaei, 2019. "Detecting critical links of urban networks using cluster detection methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 288-298.
    4. Juan Pablo Vielma & Shabbir Ahmed & George Nemhauser, 2010. "Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions," Operations Research, INFORMS, vol. 58(2), pages 303-315, April.
    5. Liu, Zhizhen & Chen, Hong & Liu, Enze & Hu, Wanyu, 2022. "Exploring the resilience assessment framework of urban road network for sustainable cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    6. Zhu, Shanjiang & Levinson, David & Liu, Henry X. & Harder, Kathleen, 2010. "The traffic and behavioral effects of the I-35W Mississippi River bridge collapse," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 771-784, December.
    7. 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.
    8. Dou, Bing-Lin & Wang, Xue-Guang & Zhang, Shi-Yong, 2010. "Robustness of networks against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(11), pages 2310-2317.
    9. Feng Xie & David Levinson, 2011. "Evaluating the effects of the I-35W bridge collapse on road-users in the twin cities metropolitan region," Transportation Planning and Technology, Taylor & Francis Journals, vol. 34(7), pages 691-703, April.
    10. An, Xin-lei & Zhang, Li & Zhang, Jian-gang, 2015. "Research on urban public traffic network with multi-weights based on single bus transfer junction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 748-755.
    11. Wang, David Z.W. & Lo, Hong K., 2010. "Global optimum of the linearized network design problem with equilibrium flows," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 482-492, May.
    12. Ke Han & Gabriel Eve & Terry L. Friesz, 2019. "Computing Dynamic User Equilibria on Large-Scale Networks with Software Implementation," Networks and Spatial Economics, Springer, vol. 19(3), pages 869-902, September.
    13. 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.
    14. 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.
    15. 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.
    16. Xueyan Wei & Wei Wang & Weijie Yu & Xuedong Hua & Yun Xiang, 2020. "A Stochastic User Equilibrium Model Under Traffic Rationing Based on Mode Shifting Rate," Sustainability, MDPI, vol. 12(13), pages 1-21, July.
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    1. Barati, Hojjat & Yazici, Anil & Almotahari, Amirmasoud, 2024. "A methodology for ranking of critical links in transportation networks based on criticality score distributions," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    2. Iliopoulou, Christina & Makridis, Michail A., 2023. "Critical multi-link disruption identification for public transport networks: A multi-objective optimization framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    3. Jin, Kun & Wang, Wei & Li, Xinran & Chen, Siyuan & Qin, Shaoyang & Hua, Xuedong, 2023. "Cascading failure in urban rail transit network considering demand variation and time delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Guo, Bao & Li, Minglun & Zhou, Mengnan & Zhang, Fan & Wang, Pu, 2023. "A new anomalous travel demand prediction method combining Markov model and complex network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    5. Qiang Tu & Han He & Xiaomin Lai & Chuan Jiang & Zhanji Zheng, 2024. "Identifying Critical Links in Degradable Road Networks Using a Traffic Demand-Based Indicator," Sustainability, MDPI, vol. 16(18), pages 1-20, September.

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