IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v581y2021ics0378437121004702.html
   My bibliography  Save this article

Transfer network of high-speed rail and aviation: Structure and critical components

Author

Listed:
  • Feng, Xiao
  • He, Shiwei
  • Li, Guangye
  • Chi, Jushang

Abstract

In this paper, we utilize network theory to model and study the coupled high-speed rail–aviation network (HSR–AN) in China. The HSR–AN depicting the transport services is modelled as a transfer network in P-space (TNP) in this research. The basic topology properties of the TNP and the corresponding critical components (e.g., nodes and areas) are analysed. As one type of spatial networks coupled two transportation networks, TNP of HSR–AN, counterintuitively, exhibits small-world properties which can be attributed by offering service connecting long-distance cities without transfer and complementary relationship between two transport modes. Additionally, an analysis of vital node (area) in vulnerability environment indicates that the importance of network components critically depends on the economic development level, population density, and geographical features in the corresponding city. Besides, the failure of high-speed rail station generates worse effect than that on airport in HSR–ANs. The findings are beneficial for enhancing the efficiency of HSR–ANs and developing emergency response plans for transport managers.

Suggested Citation

  • Feng, Xiao & He, Shiwei & Li, Guangye & Chi, Jushang, 2021. "Transfer network of high-speed rail and aviation: Structure and critical components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
  • Handle: RePEc:eee:phsmap:v:581:y:2021:i:c:s0378437121004702
    DOI: 10.1016/j.physa.2021.126197
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121004702
    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.2021.126197?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. Song, Zhichao & Ge, Yuanzheng & Luo, Lei & Duan, Hong & Qiu, Xiaogang, 2015. "An effective immunization strategy for airborne epidemics in modular and hierarchical social contact network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 142-149.
    2. 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.
    3. C. von Ferber & T. Holovatch & Yu. Holovatch & V. Palchykov, 2009. "Public transport networks: empirical analysis and modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(2), pages 261-275, March.
    4. Parthasarathi, Pavithra & Levinson, David, 2018. "Network structure and the journey to work: An intra-metropolitan analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 292-304.
    5. He, Sylvia Y., 2020. "Regional impact of rail network accessibility on residential property price: Modelling spatial heterogeneous capitalisation effects in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 244-263.
    6. Shanmukhappa, Tanuja & Ho, Ivan Wang-Hei & Tse, Chi Kong, 2018. "Spatial analysis of bus transport networks using network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 295-314.
    7. Liu, Shuli & Wan, Yulai & Zhang, Anming, 2020. "Does China’s high-speed rail development lead to regional disparities? A network perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 299-321.
    8. 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.
    9. Yu, Senbin & Gao, Liang & Xu, Lida & Gao, Zi-You, 2019. "Identifying influential spreaders based on indirect spreading in neighborhood," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 418-425.
    10. Zhou, Yaoming & Wang, Junwei & Huang, George Q., 2019. "Efficiency and robustness of weighted air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 14-26.
    11. Xu, Wangtu (Ato) & Zhou, Jiangping & Qiu, Guo, 2018. "China's high-speed rail network construction and planning over time: a network analysis," Journal of Transport Geography, Elsevier, vol. 70(C), pages 40-54.
    12. 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).
    13. Matisziw, T.C. & Grubesic, T.H., 2010. "Evaluating locational accessibility to the US air transportation system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 710-722, November.
    14. Li, Tao & Rong, Lili & Zhang, Anming, 2021. "Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail," Transport Policy, Elsevier, vol. 106(C), pages 226-238.
    15. Lordan, Oriol & Sallan, Jose M., 2019. "Core and critical cities of global region airport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 724-733.
    16. Mengqiao Xu & Qian Pan & Alessandro Muscoloni & Haoxiang Xia & Carlo Vittorio Cannistraci, 2020. "Modular gateway-ness connectivity and structural core organization in maritime network science," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
    17. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2021. "Comparative accessibility of Chinese airports and high-speed railway stations: A high-resolution, yet scalable framework based on open data," Journal of Air Transport Management, Elsevier, vol. 92(C).
    18. 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.
    19. 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.
    20. Roger Guimerà & Luís A. Nunes Amaral, 2005. "Functional cartography of complex metabolic networks," Nature, Nature, vol. 433(7028), pages 895-900, February.
    21. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    22. Ding Luo & Oded Cats & Hans Lint, 2020. "Can passenger flow distribution be estimated solely based on network properties in public transport systems?," Transportation, Springer, vol. 47(6), pages 2757-2776, December.
    23. Li, W. & Cai, X., 2007. "Empirical analysis of a scale-free railway network in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 693-703.
    24. Li, Xianghua & Guo, Jingyi & Gao, Chao & Su, Zhen & Bao, Deng & Zhang, Zili, 2018. "Network-based transportation system analysis: A case study in a mountain city," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 256-265.
    25. Wandelt, Sebastian & Shi, Xing & Sun, Xiaoqian, 2021. "Estimation and improvement of transportation network robustness by exploiting communities," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    26. Ouyang, Min, 2016. "Critical location identification and vulnerability analysis of interdependent infrastructure systems under spatially localized attacks," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 106-116.
    27. Alessandro Vespignani, 2018. "Twenty years of network science," Nature, Nature, vol. 558(7711), pages 528-529, June.
    28. Su, Min & Luan, Weixin & Fu, Xiaowen & Yang, Zaili & Zhang, Rui, 2020. "The competition effects of low-cost carriers and high-speed rail on the Chinese aviation market," Transport Policy, Elsevier, vol. 95(C), pages 37-46.
    29. Chen, Yu & Wang, Jiaoe & Jin, Fengjun, 2020. "Robustness of China’s air transport network from 1975 to 2017," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    30. Zhang, Wenjun & Deng, Weibing & Li, Wei, 2018. "Statistical properties of links of network: A survey on the shipping lines of Worldwide Marine Transport Network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 218-227.
    31. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    32. Liang Tian & Amir Bashan & Da-Ning Shi & Yang-Yu Liu, 2017. "Articulation points in complex networks," Nature Communications, Nature, vol. 8(1), pages 1-9, April.
    33. Hong, Inho & Jung, Woo-Sung, 2016. "Application of gravity model on the Korean urban bus network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 48-55.
    34. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Comparison analysis on complex topological network models of urban rail transit: A case study of Shenzhen Metro in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    35. Ouyang, Min & Pan, ZheZhe & Hong, Liu & He, Yue, 2015. "Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 248-257.
    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. Abdelaty, Hatem & Mohamed, Moataz & Ezzeldin, Mohamed & El-Dakhakhni, Wael, 2022. "Temporal robustness assessment framework for city-scale bus transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(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. Li, Tao & Rong, Lili, 2021. "Impacts of service feature on vulnerability analysis of high-speed rail network," Transport Policy, Elsevier, vol. 110(C), pages 238-253.
    2. Li, Tao & Rong, Lili, 2022. "Spatiotemporally complementary effect of high-speed rail network on robustness of aviation network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 95-114.
    3. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Hu, Xinlei & Huang, Jie & Shi, Feng, 2022. "A robustness assessment with passenger flow data of high-speed rail network in China," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    5. Chao Fang & Piao Dong & Yi-Ping Fang & Enrico Zio, 2020. "Vulnerability analysis of critical infrastructure under disruptions: An application to China Railway High-speed," Journal of Risk and Reliability, , vol. 234(2), pages 235-245, April.
    6. 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).
    7. Abdelaty, Hatem & Mohamed, Moataz & Ezzeldin, Mohamed & El-Dakhakhni, Wael, 2022. "Temporal robustness assessment framework for city-scale bus transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    8. 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.
    9. Zhou, Zhengyi & Zhang, Anming, 2021. "High-speed rail and industrial developments: Evidence from house prices and city-level GDP in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 98-113.
    10. Xiaoqian Sun & Sebastian Wandelt, 2021. "Robustness of Air Transportation as Complex Networks:Systematic Review of 15 Years of Research and Outlook into the Future," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
    11. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Exploring node importance evolution of weighted complex networks in urban rail transit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    12. Liu, Xueli & Jiang, Chunxia & Wang, Feng & Yao, Shujie, 2021. "The impact of high-speed railway on urban housing prices in China: A network accessibility perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 84-99.
    13. 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).
    14. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    15. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Sheu, Jiuh-Biing, 2021. "Spatiotemporal variation of the worldwide air transportation network induced by COVID-19 pandemic in 2020," Transport Policy, Elsevier, vol. 111(C), pages 168-184.
    16. Peng Wu & Yunfei Li & Chengbing Li, 2022. "Invulnerability of the Urban Agglomeration Integrated Passenger Transport Network under Emergency Events," IJERPH, MDPI, vol. 20(1), pages 1-16, December.
    17. Li, Tao & Rong, Lili & Zhang, Anming, 2021. "Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail," Transport Policy, Elsevier, vol. 106(C), pages 226-238.
    18. Shen, Jingwei & Zong, Huiming, 2023. "Identification of critical transportation cities in the multimodal transportation network of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    19. Gu, Yu & Chen, Anthony & Xu, Xiangdong, 2023. "Measurement and ranking of important link combinations in the analysis of transportation network vulnerability envelope buffers under multiple-link disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 118-144.
    20. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(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:581:y:2021:i:c:s0378437121004702. 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.