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Impacts of service feature on vulnerability analysis of high-speed rail network

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  • Li, Tao
  • Rong, Lili

Abstract

While previous literatures have analyzed the vulnerability of high-speed rail network (HSRN), they rarely consider its service feature. Obviously, one of the key features of HSRN is offering passengers fast travel services. This study selects the passenger flow and travel time to describe the service feature of HSRN, and constructs a multiple-weight HSRN. Then, the service performance is taken as the indicator of HSRN's vulnerability by innovatively integrating complex network theory and reliability theory. Using the daily operation data of China's HSRN (CHSRN) merged with the coordinate data and statistics data in November 2018, this study assesses its vulnerability under natural hazards and manmade accidents. Afterwards, the critical component and critical area within CHSRN are identified by the spatially localized failures (SLFs) model. Comparing with the results obtained by previous methods, this study finds that the vulnerability of CHSRN is always overestimated, and some critical components are overlooked regardless of its service feature. Furthermore, we also find that the critical areas within CHSRN mostly lie on the Yangtze River Delta as considering the service feature, while they are scattered along Beijing-Guangzhou railway line or Beijing-Shanghai railway line as ignoring the feature. These findings can help administrators develop different strategies to better prioritize the allocation of limited maintenance resources and mitigate the vulnerability of HSRN.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:trapol:v:110:y:2021:i:c:p:238-253
    DOI: 10.1016/j.tranpol.2021.05.012
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    as
    1. Wang, Kun & Xia, Wenyi & Zhang, Anming & Zhang, Qiong, 2018. "Effects of train speed on airline demand and price: Theory and empirical evidence from a natural experiment," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 99-130.
    2. Min Ouyang & Hui Tian & Zhenghua Wang & Liu Hong & Zijun Mao, 2019. "Critical Infrastructure Vulnerability to Spatially Localized Failures with Applications to Chinese Railway System," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 180-194, January.
    3. Xu, Wangtu (Ato) & Long, Ying & Zhang, Wei, 2019. "Prioritizing future funding and construction of the planned high-speed rail corridors of China – According to regional structure and urban land development potential indices," Transport Policy, Elsevier, vol. 81(C), pages 381-395.
    4. Chen, Zhenhua & Wang, Yuxuan & Zhou, Lei, 2021. "Predicting weather-induced delays of high-speed rail and aviation in China," Transport Policy, Elsevier, vol. 101(C), pages 1-13.
    5. Alexander Erath & Michael Löchl & Kay Axhausen, 2009. "Graph-Theoretical Analysis of the Swiss Road and Railway Networks Over Time," Networks and Spatial Economics, Springer, vol. 9(3), pages 379-400, September.
    6. 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.
    7. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    8. López, Fernando A. & Páez, Antonio & Carrasco, Juan A. & Ruminot, Natalia A., 2017. "Vulnerability of nodes under controlled network topology and flow autocorrelation conditions," Journal of Transport Geography, Elsevier, vol. 59(C), pages 77-87.
    9. Zhang, Jianhua & Hu, Funian & Wang, Shuliang & Dai, Yang & Wang, Yixing, 2016. "Structural vulnerability and intervention of high speed railway networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 743-751.
    10. Milan Janić, 2018. "Modelling the resilience of rail passenger transport networks affected by large-scale disruptive events: the case of HSR (high speed rail)," Transportation, Springer, vol. 45(4), pages 1101-1137, July.
    11. Laurino, Antonio & Ramella, Francesco & Beria, Paolo, 2015. "The economic regulation of railway networks: A worldwide survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 202-212.
    12. Jiang, Ruoyun & Lu, Qing-Chang & Peng, Zhong-Ren, 2018. "A station-based rail transit network vulnerability measure considering land use dependency," Journal of Transport Geography, Elsevier, vol. 66(C), pages 10-18.
    13. 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).
    14. Sun, Xiaoqian & Wandelt, Sebastian & Zheng, Changhong & Zhang, Anming, 2021. "COVID-19 pandemic and air transportation: Successfully navigating the paper hurricane," Journal of Air Transport Management, Elsevier, vol. 94(C).
    15. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    16. 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.
    17. 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.
    18. Huang, Yuxia & Jiang, Chenxin & Wang, Kun & Xiao, Yibin & Zhang, Anming, 2021. "Public-private partnership in high-speed rail financing: Case of uncertain regional economic spillovers in China," Transport Policy, Elsevier, vol. 106(C), pages 64-75.
    19. Vickerman, Roger, 2018. "Can high-speed rail have a transformative effect on the economy?," Transport Policy, Elsevier, vol. 62(C), pages 31-37.
    20. Moyano, Amparo & Martínez, Héctor S. & Coronado, José M., 2018. "From network to services: A comparative accessibility analysis of the Spanish high-speed rail system," Transport Policy, Elsevier, vol. 63(C), pages 51-60.
    21. 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.
    22. Ma, Wenliang & Wang, Qiang & Yang, Hangjun & Zhang, Anming & Zhang, Yahua, 2019. "Effects of Beijing-Shanghai high-speed rail on air travel: Passenger types, airline groups and tacit collusion," Research in Transportation Economics, Elsevier, vol. 74(C), pages 64-76.
    23. Zhang, Anming & Wan, Yulai & Yang, Hangjun, 2019. "Impacts of high-speed rail on airlines, airports and regional economies: A survey of recent research," Transport Policy, Elsevier, vol. 81(C), pages 1-19.
    24. Wang, Lei, 2018. "High-speed rail services development and regional accessibility restructuring in megaregions: A case of the Yangtze River Delta, China," Transport Policy, Elsevier, vol. 72(C), pages 34-44.
    25. 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.
    26. Jiao, Jingjuan & Wang, Jiaoe & Jin, Fengjun, 2017. "Impacts of high-speed rail lines on the city network in China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 257-266.
    27. Yang, Hangjun & Zhang, Anming, 2012. "Effects of high-speed rail and air transport competition on prices, profits and welfare," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1322-1333.
    28. Zhang, Fangni & Graham, Daniel J. & Wong, Mark Siu Chun, 2018. "Quantifying the substitutability and complementarity between high-speed rail and air transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 191-215.
    29. 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.
    30. Wang, Kun & Jiang, Changmin & Ng, Adolf K.Y. & Zhu, Zhenran, 2020. "Air and rail connectivity patterns of major city clusters in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 35-53.
    31. Zhang, Wenxin & Nian, Peihao & Lyu, Guowei, 2016. "A multimodal approach to assessing accessibility of a high-speed railway station," Journal of Transport Geography, Elsevier, vol. 54(C), pages 91-101.
    32. 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.
    33. Li, Yan & Chen, Zhenhua & Wang, Peng, 2020. "Impact of high-speed rail on urban economic efficiency in China," Transport Policy, Elsevier, vol. 97(C), pages 220-231.
    34. 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.
    35. Zhang, Qiong & Yang, Hangjun & Wang, Qiang & Zhang, Anming & Zhang, Yahua, 2020. "Impact of high-speed rail on market concentration and Lerner index in China's airline market," Journal of Air Transport Management, Elsevier, vol. 83(C).
    36. 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.
    37. Szymula, Christopher & Bešinović, Nikola, 2020. "Passenger-centered vulnerability assessment of railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 30-61.
    38. Yang, Hangjun & Ma, Wenliang & Wang, Qiang & Wang, Kun & Zhang, Yahua, 2020. "Welfare implications for air passengers in China in the era of high-speed rail," Transport Policy, Elsevier, vol. 95(C), pages 1-13.
    39. Zhang, Rui & Johnson, Daniel & Zhao, Weiming & Nash, Chris, 2019. "Competition of airline and high-speed rail in terms of price and frequency: Empirical study from China," Transport Policy, Elsevier, vol. 78(C), pages 8-18.
    40. Hsieh, Cheng-Hsien & Feng, Cheng-Min, 2020. "The highway resilience and vulnerability in Taiwan," Transport Policy, Elsevier, vol. 87(C), pages 1-9.
    41. Wang, Jiaoe & Mo, Huihui & Wang, Fahui & Jin, Fengjun, 2011. "Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach," Journal of Transport Geography, Elsevier, vol. 19(4), pages 712-721.
    42. Clewlow, Regina R. & Sussman, Joseph M. & Balakrishnan, Hamsa, 2014. "The impact of high-speed rail and low-cost carriers on European air passenger traffic," Transport Policy, Elsevier, vol. 33(C), pages 136-143.
    43. Li, Hongchang & Strauss, Jack & Lu, Liu, 2019. "The impact of high-speed rail on civil aviation in China," Transport Policy, Elsevier, vol. 74(C), pages 187-200.
    44. 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.
    45. Yahua Zhang & Faqin Lin & Anming Zhang, 2018. "Gravity models in air transport research: a survey and an application," Chapters, in: Bruce A. Blonigen & Wesley W. Wilson (ed.), Handbook of International Trade and Transportation, chapter 4, pages 141-158, Edward Elgar Publishing.
    46. Kim, Hyojin & Sultana, Selima & Weber, Joe, 2018. "A geographic assessment of the economic development impact of Korean high-speed rail stations," Transport Policy, Elsevier, vol. 66(C), pages 127-137.
    47. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    48. Faturechi, Reza & Miller-Hooks, Elise, 2014. "Travel time resilience of roadway networks under disaster," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 47-64.
    49. 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.
    50. Campos, Javier & de Rus, Ginés, 2009. "Some stylized facts about high-speed rail: A review of HSR experiences around the world," Transport Policy, Elsevier, vol. 16(1), pages 19-28, January.
    51. Ren, Xiaohong & Chen, Zhenhua & Wang, Fang & Dan, Ting & Wang, Wei & Guo, Xiaotong & Liu, Chunhua, 2020. "Impact of high-speed rail on social equity in China: Evidence from a mode choice survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 422-441.
    52. Zhenhua Chen, 2019. "Measuring the regional economic impacts of high-speed rail using a dynamic SCGE model: the case of China," European Planning Studies, Taylor & Francis Journals, vol. 27(3), pages 483-512, March.
    53. 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.
    54. Snelder, M. & van Zuylen, H.J. & Immers, L.H., 2012. "A framework for robustness analysis of road networks for short term variations in supply," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 828-842.
    55. Hong, Liu & Zhong, Xin & Ouyang, Min & Tian, Hui & He, Xiaozheng, 2019. "Vulnerability analysis of public transit systems from the perspective of urban residential communities," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 143-156.
    56. Wang, Feng & Wei, Xianjin & Liu, Juan & He, Lingyun & Gao, Mengnan, 2019. "Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 99-114.
    57. Sun, Lishan & Huang, Yuchen & Chen, Yanyan & Yao, Liya, 2018. "Vulnerability assessment of urban rail transit based on multi-static weighted method in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 108(C), pages 12-24.
    58. 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.
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