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A study of the U.S. domestic air transportation network: temporal evolution of network topology and robustness from 2001 to 2016

Author

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  • Leonidas Siozos-Rousoulis

    (Innovation and Networks Executive Agency of the European Commission
    Vrije Universiteit Brussel (VUB))

  • Dimitri Robert

    (Vrije Universiteit Brussel (VUB))

  • Wouter Verbeke

    (KU Leuven)

Abstract

The U.S. air transportation network (ATN) is critical to the mobility and the functioning of the United States. It is thus necessary to ensure that it is well-connected, efficient, robust, and secure. Despite extensive research on its topology, the temporal evolution of the network’s robustness remains largely unexplored. In the present paper, a methodology is proposed to identify long-term trends in the evolution of the network’s topology and robustness over time. The study of the U.S. domestic ATN’s robustness was performed based on annual flight data from 1996 to 2016 and network analytics were used to examine the effects of restructuring that followed the 9/11 events. Centrality measures were computed and a node deletion method was applied to assess the network’s tolerance to a targeted attack scenario. The outcome of this study indicated that the 9/11 terrorist attacks triggered vast restructuring of the network, in terms of efficiency and security. Air traffic expanded, as new airports and air routes were introduced, allowing the network to recover rapidly and become more efficient. Security concerns resulted in significant improvement of the network’s robustness. Since 2001, the global traffic and topological properties of the U.S. ATN have displayed continuous growth, due to the network’s expansion. On the other hand, the results suggest that although the system’s ability to sustain its operational level under extreme circumstances has lately improved, its tolerance to targeted attacks has deteriorated. The presented methodology has shown its potential to be applied on different network levels or different transportation networks, in order to provide a general perspective of the system’s vulnerabilities.

Suggested Citation

  • Leonidas Siozos-Rousoulis & Dimitri Robert & Wouter Verbeke, 2021. "A study of the U.S. domestic air transportation network: temporal evolution of network topology and robustness from 2001 to 2016," Journal of Transportation Security, Springer, vol. 14(1), pages 55-78, June.
  • Handle: RePEc:spr:jtrsec:v:14:y:2021:i:1:d:10.1007_s12198-020-00227-x
    DOI: 10.1007/s12198-020-00227-x
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    References listed on IDEAS

    as
    1. Jia, Tao & Qin, Kun & Shan, Jie, 2014. "An exploratory analysis on the evolution of the US airport network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 266-279.
    2. Janić, Milan, 2015. "Reprint of “Modelling the resilience, friability and costs of an air transport network affected by a large-scale disruptive event”," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 77-92.
    3. Dobruszkes, Frédéric & Van Hamme, Gilles, 2011. "The impact of the current economic crisis on the geography of air traffic volumes: an empirical analysis," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1387-1398.
    4. Lordan, Oriol & Sallan, Jose M. & Simo, Pep, 2014. "Study of the topology and robustness of airline route networks from the complex network approach: a survey and research agenda," Journal of Transport Geography, Elsevier, vol. 37(C), pages 112-120.
    5. Gelhausen, Marc C. & Berster, Peter & Wilken, Dieter, 2013. "Do airport capacity constraints have a serious impact on the future development of air traffic?," Journal of Air Transport Management, Elsevier, vol. 28(C), pages 3-13.
    6. Wandelt, Sebastian & Sun, Xiaoqian, 2015. "Evolution of the international air transportation country network from 2002 to 2013," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 55-78.
    7. repec:bla:revpol:v:21:y:2004:i:3:p:275-291 is not listed on IDEAS
    8. Upham, Paul & Thomas, Callum & Gillingwater, David & Raper, David, 2003. "Environmental capacity and airport operations: current issues and future prospects," Journal of Air Transport Management, Elsevier, vol. 9(3), pages 145-151.
    9. 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.
    10. 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.
    11. Franke, Markus, 2004. "Competition between network carriers and low-cost carriers—retreat battle or breakthrough to a new level of efficiency?," Journal of Air Transport Management, Elsevier, vol. 10(1), pages 15-21.
    12. Zhang, Jun & Cao, Xian-Bin & Du, Wen-Bo & Cai, Kai-Quan, 2010. "Evolution of Chinese airport network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3922-3931.
    13. Frédéric Dobruszkes & Gilles Van Hamme, 2011. "The impact of the current economic crisis on the geography of air traffic volumes: an empirical analysis," ULB Institutional Repository 2013/96228, ULB -- Universite Libre de Bruxelles.
    14. Lichun Chen & Elise Miller-Hooks, 2012. "Resilience: An Indicator of Recovery Capability in Intermodal Freight Transport," Transportation Science, INFORMS, vol. 46(1), pages 109-123, February.
    15. Ito, Harumi & Lee, Darin, 2005. "Assessing the impact of the September 11 terrorist attacks on U.S. airline demand," Journal of Economics and Business, Elsevier, vol. 57(1), pages 75-95.
    16. Chi, Junwook & Baek, Jungho, 2013. "Dynamic relationship between air transport demand and economic growth in the United States: A new look," Transport Policy, Elsevier, vol. 29(C), pages 257-260.
    17. Nancy L. Rose, 2014. "Economic Regulation and Its Reform: What Have We Learned?," NBER Books, National Bureau of Economic Research, Inc, number rose05-1.
    18. Sen, Amartya, 1973. "On Economic Inequality," OUP Catalogue, Oxford University Press, number 9780198281931.
    19. Reggiani, Aura, 2013. "Network resilience for transport security: Some methodological considerations," Transport Policy, Elsevier, vol. 28(C), pages 63-68.
    20. Gillen, David & Morrison, William G., 2005. "Regulation, competition and network evolution in aviation," Journal of Air Transport Management, Elsevier, vol. 11(3), pages 161-174.
    21. Janić, Milan, 2015. "Modelling the resilience, friability and costs of an air transport network affected by a large-scale disruptive event," Transportation Research Part A: Policy and Practice, Elsevier, vol. 71(C), pages 1-16.
    22. Dai, Liang & Derudder, Ben & Liu, Xingjian, 2018. "The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979–2012," Journal of Transport Geography, Elsevier, vol. 68(C), pages 67-77.
    23. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
    24. Redondi, Renato & Malighetti, Paolo & Paleari, Stefano, 2012. "De-hubbing of airports and their recovery patterns," Journal of Air Transport Management, Elsevier, vol. 18(1), pages 1-4.
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