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Parameterized framework for the analysis of probabilities of aircraft delay at an airport

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  • Wesonga, Ronald
  • Nabugoomu, Fabian
  • Jehopio, Peter

Abstract

The study analyses ground delays and air holding at Entebbe International Airport over five years. Daily probabilities for aircraft departure and arrival delays at are generated for each. The mean probabilities of delay for ground delays and air holding at 50% delay threshold levels are 0.94 and 0.82 that fall to 0.49 and 0.36 when 60% delay threshold levels are used. Simulations are performance for delay threshold levels to monitor for the trends of the daily probabilities for the study period. The general conclusion is that a parameter-based framework is best suited to determine the probability of aircraft delay at an airport.

Suggested Citation

  • Wesonga, Ronald & Nabugoomu, Fabian & Jehopio, Peter, 2012. "Parameterized framework for the analysis of probabilities of aircraft delay at an airport," Journal of Air Transport Management, Elsevier, vol. 23(C), pages 1-4.
    • Handle: RePEc:eee:jaitra:v:23:y:2012:i:c:p:1-4
    DOI: 10.1016/j.jairtraman.2012.02.001
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    References listed on IDEAS

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    1. Tu, Yufeng & Ball, Michael O. & Jank, Wolfgang S., 2008. "Estimating Flight Departure Delay DistributionsA Statistical Approach With Long-Term Trend and Short-Term Pattern," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 112-125, March.
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    Cited by:

    1. Wesonga, Ronald, 2015. "Airport utility stochastic optimization models for air traffic flow management," European Journal of Operational Research, Elsevier, vol. 242(3), pages 999-1007.
    2. de Oliveira, McWillian & Eufrásio, Ana Beatriz Rebouças & Guterres, Marcelo Xavier & Murça, Mayara Condé Rocha & Gomes, Rogéria de Arantes, 2021. "Analysis of airport weather impact on on-time performance of arrival flights for the Brazilian domestic air transportation system," Journal of Air Transport Management, Elsevier, vol. 91(C).
    3. Yu, Bin & Guo, Zhen & Asian, Sobhan & Wang, Huaizhu & Chen, Gang, 2019. "Flight delay prediction for commercial air transport: A deep learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 203-221.
    4. Kim, Myeonghyeon & Park, Sunwook, 2021. "Airport and route classification by modelling flight delay propagation," Journal of Air Transport Management, Elsevier, vol. 93(C).

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