IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v654y2024ics0378437124006289.html
   My bibliography  Save this article

Abnormal cascading dynamics in transportation networks based on Gaussian distribution of load

Author

Listed:
  • Wang, Jianwei
  • Li, Yiwen
  • He, Haofan
  • He, Rouye

Abstract

In the transportation network, we observe that the distance people travel by means of transportation follows a certain distribution. Statistical analysis shows that people’s travel distance is mainly concentrated in a medium range by the same vehicle, and they choose fewer destinations that are extremely close or far away. However, in previous studies, the impact of distance on the distribution of load flow within the network has often been neglected, or at best, addressed with overly simplistic assumptions. Therefore, we quantify the load flow distribution based on the Gaussian distribution of distances between the nodes. On this basis, a new cascading failure model is proposed using the shortest path strategy to calculate the initial load of the edge. Through the simulation of three real traffic networks and two artificially constructed networks with similar structural characteristics of traffic networks, we found the following interesting anomalies: First, increasing the load-bearing capacity of edges within the network does not necessarily lead to enhanced robustness. Second, we observed that removing more edges does not necessarily lead to a decrease in network robustness; conversely, the network robustness can be higher when a moderate number of edges are removed compared to fewer edges. To better understand the two anomalous dynamics phenomena we observed, we ran simulations on a small-scale network extracted from a real traffic network. We found that, under certain circumstances, the premature failure of some edges may isolate certain regions from the network, which may be responsible for this paradox.

Suggested Citation

  • Wang, Jianwei & Li, Yiwen & He, Haofan & He, Rouye, 2024. "Abnormal cascading dynamics in transportation networks based on Gaussian distribution of load," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 654(C).
  • Handle: RePEc:eee:phsmap:v:654:y:2024:i:c:s0378437124006289
    DOI: 10.1016/j.physa.2024.130119
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124006289
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2024.130119?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. Xia, Yongxiang & Wang, Cong & Shen, Hui-Liang & Song, Hainan, 2020. "Cascading failures in spatial complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    2. Wang, Jianwei & Zhao, Naixuan & Xiang, Linghui & Wang, Chupei, 2023. "Abnormal cascading dynamics based on the perspective of road impedance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).
    3. Storm, Pieter Jacob & Mandjes, Michel & van Arem, Bart, 2022. "Efficient evaluation of stochastic traffic flow models using Gaussian process approximation," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 126-144.
    4. Peng, Xingzhao & Yao, Hong & Du, Jun & Wang, Zhe & Ding, Chao, 2015. "Invulnerability of scale-free network against critical node failures based on a renewed cascading failure model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 69-77.
    5. Zhenggang He & Jing-Ni Guo & Jun-Xiang Xu, 2019. "Cascade Failure Model in Multimodal Transport Network Risk Propagation," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-7, December.
    6. Jin, Yi & Zhang, Qingyuan & Chen, Yunxia & Lu, Zhendan & Zu, Tianpei, 2023. "Cascading failures modeling of electronic circuits with degradation using impedance network," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    7. Yin, Dezhi & Huang, Wencheng & Shuai, Bin & Liu, Hongyi & Zhang, Yue, 2022. "Structural characteristics analysis and cascading failure impact analysis of urban rail transit network: From the perspective of multi-layer network," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. Zhang, Lin & Wen, Huiying & Lu, Jian & Lei, Da & Li, Shubin & Ukkusuri, Satish V., 2022. "Exploring cascading reliability of multi-modal public transit network based on complex networks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    9. Jin, Ziyang & Duan, Dongli & Wang, Ning, 2022. "Cascading failure of complex networks based on load redistribution and epidemic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    10. Hong Liu & Yunyan Han & Jinlong Ni & Anding Zhu & A. M. Bastos Pereira, 2022. "Modelling Underload Cascading Failure and Mitigation Strategy of Supply Chain Complex Network in COVID-19," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, February.
    11. Renjian Lyu & Min Zhang & Xiao-Juan Wang & Tie-Jun Wang, 2022. "Recovery strategy of multilayer network against cascading failure," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 33(03), pages 1-18, March.
    12. Zheng, Jian-Feng & Gao, Zi-You & Zhao, Xiao-Mei, 2007. "Modeling cascading failures in congested complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 700-706.
    13. Jing, Ke & Du, Xinru & Shen, Lixin & Tang, Liang, 2019. "Robustness of complex networks: Cascading failure mechanism by considering the characteristics of time delay and recovery strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    14. Wu, J.J. & Sun, H.J. & Gao, Z.Y., 2007. "Cascading failures on weighted urban traffic equilibrium networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 407-413.
    15. Xue, Fei & Bompard, Ettore & Huang, Tao & Jiang, Lin & Lu, Shaofeng & Zhu, Huaiying, 2017. "Interrelation of structure and operational states in cascading failure of overloading lines in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 728-740.
    16. Wang, Jianwei & Cai, Lin & Xu, Bo & Li, Peng & Sun, Enhui & Zhu, Zhiguo, 2016. "Out of control: Fluctuation of cascading dynamics in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1231-1243.
    17. Chen, Shi-Ming & Xu, Yun-Fei & Nie, Sen, 2017. "Robustness of network controllability in cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 536-539.
    18. Fu, Xiuwen & Yang, Yongsheng, 2020. "Modeling and analysis of cascading node-link failures in multi-sink wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    19. Jianwei Wang & Chen Jiang & Jianfei Qian, 2013. "Improving Robustness Of Coupled Networks Against Cascading Failures," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(11), pages 1-12.
    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. Wang, Jianwei & Zhao, Naixuan & Xiang, Linghui & Wang, Chupei, 2023. "Abnormal cascading dynamics based on the perspective of road impedance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).
    2. Huang, Wencheng & Zhou, Bowen & Yu, Yaocheng & Sun, Hao & Xu, Pengpeng, 2021. "Using the disaster spreading theory to analyze the cascading failure of urban rail transit network," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Shen, Yi & Yang, Huang & Xie, Yuangcheng & Liu, Yang & Ren, Gang, 2023. "Adaptive robustness optimization against network cascading congestion induced by fluctuant load via a bilateral-adaptive strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Yin, Rongrong & Zhang, Kai & Ma, Xuyao & Wang, Yumeng & Li, Linhui, 2023. "Analysis of cascading failures caused by mobile overload attacks in scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    5. Lu, Qing-Chang & Li, Jing & Xu, Peng-Cheng & Zhang, Lei & Cui, Xin, 2024. "Modeling cascading failures of urban rail transit network based on passenger spatiotemporal heterogeneity," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    6. Guo, Jingni & Xu, Junxiang & He, Zhenggang & Liao, Wei, 2021. "Research on risk propagation method of multimodal transport network under uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    7. Zhang, Lin & Wen, Huiying & Lu, Jian & Lei, Da & Li, Shubin & Ukkusuri, Satish V., 2022. "Exploring cascading reliability of multi-modal public transit network based on complex networks," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    8. Yang, Qihui & Scoglio, Caterina M. & Gruenbacher, Don M., 2021. "Robustness of supply chain networks against underload cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    9. 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).
    10. Fu, Xiuwen & Wang, Ye & Yang, Yongsheng & Postolache, Octavian, 2022. "Analysis on cascading reliability of edge-assisted Internet of Things," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    11. Lu, Qing-Chang & Zhang, Lei & Xu, Peng-Cheng & Cui, Xin & Li, Jing, 2022. "Modeling network vulnerability of urban rail transit under cascading failures: A Coupled Map Lattices approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    12. Zhang, Lin & Xu, Min & Wang, Shuaian, 2023. "Quantifying bus route service disruptions under interdependent cascading failures of a multimodal public transit system based on an improved coupled map lattice model," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    13. Ren, Hai-Peng & Song, Jihong & Yang, Rong & Baptista, Murilo S. & Grebogi, Celso, 2016. "Cascade failure analysis of power grid using new load distribution law and node removal rule," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 239-251.
    14. Lin Zhang & Jian Lu & Bai-bai Fu & Shu-bin Li, 2018. "A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory," Complexity, Hindawi, vol. 2018, pages 1-36, December.
    15. Wu, Yipeng & Chen, Zhilong & Zhao, Xudong & Gong, Huadong & Su, Xiaochao & Chen, Yicun, 2021. "Propagation model of cascading failure based on discrete dynamical system," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    16. Fei Ma & Fei Liu & Kum Fai Yuen & Polin Lai & Qipeng Sun & Xiaodan Li, 2019. "Cascading Failures and Vulnerability Evolution in Bus–Metro Complex Bilayer Networks under Rainstorm Weather Conditions," IJERPH, MDPI, vol. 16(3), pages 1-30, January.
    17. Wang, Jianwei & Wang, Siyuan & Wang, Ziwei, 2022. "Robustness of spontaneous cascading dynamics driven by reachable area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    18. Al-Takrouri, Saleh & Savkin, Andrey V., 2013. "A decentralized flow redistribution algorithm for avoiding cascaded failures in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6135-6145.
    19. Meng, Yangyang & Zhao, Xiaofei & Liu, Jianzhong & Qi, Qingjie & Zhou, Wei, 2023. "Data-driven complexity analysis of weighted Shenzhen Metro network based on urban massive mobility in the rush hours," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    20. 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).

    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:phsmap:v:654:y:2024:i:c:s0378437124006289. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.