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A Queuing Model of the Airport Departure Process

Author

Listed:
  • Ioannis Simaiakis

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Hamsa Balakrishnan

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

This paper presents an analytical model of the aircraft departure process at an airport. The modeling procedure includes the estimation of unimpeded taxi-out time distributions and the development of a queuing model of the departure runway system based on the transient analysis of D / E /1 queuing systems. The parameters of the runway service process are estimated using operational data. Using the aircraft pushback schedule as input, the model predicts the expected runway schedule and takeoff times. It also estimates the expected taxi-out time, queuing delay, and its variance for each flight in addition to the congestion level of the airport, sizes of the departure runway queues, and the departure throughput. The proposed approach is illustrated using a case study based on Newark Liberty International Airport. The model is trained using data from 2011 and is subsequently used to predict taxi-out times in 2007 and 2010. The predictions are compared with actual data to demonstrate the predictive capabilities of the model.

Suggested Citation

  • Ioannis Simaiakis & Hamsa Balakrishnan, 2016. "A Queuing Model of the Airport Departure Process," Transportation Science, INFORMS, vol. 50(1), pages 94-109, February.
  • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:1:p:94-109
    DOI: 10.1287/trsc.2015.0603
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    References listed on IDEAS

    as
    1. Bernard O. Koopman, 1972. "Air-Terminal Queues under Time-Dependent Conditions," Operations Research, INFORMS, vol. 20(6), pages 1089-1114, December.
    2. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
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    Cited by:

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    2. Chen, Shuiwang & Wu, Lingxiao & Ng, Kam K.H. & Liu, Wei & Wang, Kun, 2024. "How airports enhance the environmental sustainability of operations: A critical review from the perspective of Operations Research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    3. Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    4. Pérez-Castán, Javier A. & Asensio, Beatriz & Rodríguez-Sanz, à lvaro & Ho-Huu, Vinh & Sanz, Luis Pérez & Comendador, Fernando Gómez & Valdés, Rosa M.Arnaldo, 2020. "Impact of Continuous Climb Operations in ATC workload. Case-study Palma airport," Journal of Air Transport Management, Elsevier, vol. 89(C).
    5. Birolini, Sebastian & Jacquillat, Alexandre, 2023. "Day-ahead aircraft routing with data-driven primary delay predictions," European Journal of Operational Research, Elsevier, vol. 310(1), pages 379-396.
    6. 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.
    7. Tang, Nga Yung Agnes & Wu, Cheng-Lung & Tan, David, 2020. "Evaluating the implementation of performance-based fuel uplift regulation for airline operation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 47-61.

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