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Queueing Models for Trajectory-Based Aircraft Operations

Author

Listed:
  • Tasos Nikoleris

    (Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Berkeley, Berkeley, California 94720)

  • Mark Hansen

    (Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Berkeley, Berkeley, California 94720)

Abstract

This paper develops a queueing model for aircraft arrivals at a single server under trajectory-based flight operations, which are expected to prevail in the Next Generation Air Transportation System. Aircraft are assigned scheduled times of arrival at a server, which they meet with some normally distributed stochastic error. The Clark approximation method is employed to estimate expected queueing delays, and it is shown, through comparison with simulation, that the method yields very accurate estimates. Exact results are derived for a special case in which aircraft are metered into a capacity-constrained area with constant excess time separation between them. This allows analysis of the tradeoff between the “stochastic delay” that results from imperfect adherence to metered times of arrival and the additional “deterministic delay” from metering at a headway above the minimum required.

Suggested Citation

  • Tasos Nikoleris & Mark Hansen, 2012. "Queueing Models for Trajectory-Based Aircraft Operations," Transportation Science, INFORMS, vol. 46(4), pages 501-511, November.
    • Handle: RePEc:inm:ortrsc:v:46:y:2012:i:4:p:501-511
    DOI: 10.1287/trsc.1120.0411
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Shone, Rob & Glazebrook, Kevin & Zografos, Konstantinos G., 2019. "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations," European Journal of Operational Research, Elsevier, vol. 276(2), pages 566-581.
    3. Marie-Sklaerder Vié & Nicolas Zufferey & Roel Leus, 2022. "Aircraft landing planning under uncertain conditions," Journal of Scheduling, Springer, vol. 25(2), pages 203-228, April.
    4. Kim, Amy & Hansen, Mark, 2013. "Deconstructing delay: A non-parametric approach to analyzing delay changes in single server queuing systems," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 119-133.
    5. Li, Max Z. & Ryerson, Megan S., 2019. "Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 111-130.
    6. Caccavale, Maria Virginia & Iovanella, Antonio & Lancia, Carlo & Lulli, Guglielmo & Scoppola, Benedetto, 2014. "A model of inbound air traffic: The application to Heathrow airport," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 116-122.
    7. Tasos Nikoleris & Mark Hansen, 2016. "Effect of Trajectory Prediction and Stochastic Runway Occupancy Times on Aircraft Delays," Transportation Science, INFORMS, vol. 50(1), pages 110-119, February.
    8. Carlo Lancia & Gianluca Guadagni & Sokol Ndreca & Benedetto Scoppola, 2018. "Asymptotics for the late arrivals problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 88(3), pages 475-493, December.
    9. Gwiggner, Claus & Nagaoka, Sakae, 2014. "Data and queueing analysis of a Japanese air-traffic flow," European Journal of Operational Research, Elsevier, vol. 235(1), pages 265-275.
    10. 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.
    11. 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.
    12. Jacquillat, Alexandre & Odoni, Amedeo R., 2015. "Endogenous control of service rates in stochastic and dynamic queuing models of airport congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 133-151.
    13. 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.
    14. Alexandre Jacquillat & Vikrant Vaze, 2018. "Interairline Equity in Airport Scheduling Interventions," Transportation Science, INFORMS, vol. 52(4), pages 941-964, August.
    15. Alexandre Jacquillat & Amedeo R. Odoni & Mort D. Webster, 2017. "Dynamic Control of Runway Configurations and of Arrival and Departure Service Rates at JFK Airport Under Stochastic Queue Conditions," Transportation Science, INFORMS, vol. 51(1), pages 155-176, February.
    16. Kim, Amy Miyoung, 2016. "The impacts of changing flight demands and throughput performance on airport delays through the Great Recession," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 19-34.

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