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Modeling Passenger Travel and Delays in the National Air Transportation System

Author

Listed:
  • Cynthia Barnhart

    (Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Douglas Fearing

    (Department of Information, Risk, and Operations Management, The University of Texas at Austin, Austin, Texas 78712)

  • Vikrant Vaze

    (Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755)

Abstract

Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of delay. However, recent research has demonstrated that passenger delays depend on many factors in addition to flight delays. For instance, significant passenger delays result from flight cancellations and missed connections, which themselves depend on a significant number of factors. Unfortunately, lack of publicly available passenger travel data has made it difficult for researchers to explore the nature of these relationships. In this paper, we develop methodologies to model historical travel and delays for U.S. domestic passengers. We develop a multinomial logit model for estimating historical passenger travel and extend a previously developed greedy reaccommodation heuristic for estimating the resulting passenger delays. We report and analyze the estimated passenger delays for calendar year 2007, developing insights into factors that affect the performance of the National Air Transportation System in the United States.

Suggested Citation

  • Cynthia Barnhart & Douglas Fearing & Vikrant Vaze, 2014. "Modeling Passenger Travel and Delays in the National Air Transportation System," Operations Research, INFORMS, vol. 62(3), pages 580-601, June.
    • Handle: RePEc:inm:oropre:v:62:y:2014:i:3:p:580-601
    DOI: 10.1287/opre.2014.1268
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    References listed on IDEAS

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    Cited by:

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    14. Kölker, Katrin & Lütjens, Klaus & Gollnick, Volker, 2024. "Analyzing global passenger flows based on choice modeling in the air transportation system," Journal of Air Transport Management, Elsevier, vol. 115(C).
    15. Gillen, David & Jacquillat, Alexandre & Odoni, Amedeo R., 2016. "Airport demand management: The operations research and economics perspectives and potential synergies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 495-513.
    16. 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.
    17. Jacquillat, Alexandre & Odoni, Amedeo R., 2018. "A roadmap toward airport demand and capacity management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 168-185.
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    20. Christos Nicolaides & Demetris Avraam & Luis Cueto‐Felgueroso & Marta C. González & Ruben Juanes, 2020. "Hand‐Hygiene Mitigation Strategies Against Global Disease Spreading through the Air Transportation Network," Risk Analysis, John Wiley & Sons, vol. 40(4), pages 723-740, April.
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    22. Uğur Arıkan & Sinan Gürel & M. Selim Aktürk, 2017. "Flight Network-Based Approach for Integrated Airline Recovery with Cruise Speed Control," Transportation Science, INFORMS, vol. 51(4), pages 1259-1287, November.
    23. Alexandre Jacquillat & Amedeo R. Odoni, 2015. "An Integrated Scheduling and Operations Approach to Airport Congestion Mitigation," Operations Research, INFORMS, vol. 63(6), pages 1390-1410, December.
    24. Nikolas Pyrgiotis & Amedeo Odoni, 2016. "On the Impact of Scheduling Limits: A Case Study at Newark Liberty International Airport," Transportation Science, INFORMS, vol. 50(1), pages 150-165, February.
    25. Keji Wei & Vikrant Vaze, 2018. "Modeling Crew Itineraries and Delays in the National Air Transportation System," Transportation Science, INFORMS, vol. 52(5), pages 1276-1296, October.

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