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Deconstructing delay: A non-parametric approach to analyzing delay changes in single server queuing systems

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  • Kim, Amy
  • Hansen, Mark

Abstract

This paper introduces an empirically driven, non-parametric method to isolate and estimate the effects that changes in demand and changes in throughput have on delay – in particular, arrival and departure flight delay at airport runways. Classic queuing concepts were used to develop a method by which an intermediate, or counterfactual, queuing scenario could be constructed, to isolate the delay effects due to shifts in demand and throughput. This method includes the development of a stochastic throughput function that is based entirely on data and has three key features. Firstly, the function relies on non-parametric, empirically-based probability distributions of throughput counts. Secondly, facility capacity needs not be explicitly defined, as it is implicitly included in the probability distributions of throughput. Thirdly, the throughput performance function preserves the effect of factors that cause capacity (and, therefore, throughput) to fluctuate over a given period. Temporal sequences of high, moderate, and low capacity are maintained between the observed and counterfactual scenarios. The method was applied to a case study of the three major New York area airports of LaGuardia (LGA), Newark Liberty (EWR), and John F. Kennedy (JFK), using operational data extracted from the Federal Aviation Administration’s (FAA’s) Aviation System Performance Metrics (ASPM) database. The focus was on the peak summer travel seasons of 2006 and 2007, as these airports experienced record levels of delay in 2007. The results indicate that decreases in both demand and throughput were experienced at LGA and EWR, although the decreases in throughput had more significant effects on operational delays as they increased overall at these airports. At JFK, the increase in departure throughput was not sufficient to offset the increase in departure demands. For arrivals, demand increased and throughput decreased. These trends caused a significant growth in delay at JFK between 2006 and 2007.

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  • 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.
    • Handle: RePEc:eee:transb:v:58:y:2013:i:c:p:119-133
    DOI: 10.1016/j.trb.2013.10.001
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    References listed on IDEAS

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    Cited by:

    1. Branko Bubalo, 2021. "Airport Capacity and Performance in Europe -- A study of transport economics, service quality and sustainability," Papers 2102.02379, arXiv.org.
    2. 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.
    3. Bubalo, Branko, 2021. "Airport Capacity and Performance in Europe - A study of transport economics, service quality and sustainability," EconStor Theses, ZBW - Leibniz Information Centre for Economics, number 229442, September.
    4. Yi Liu & Mark Hansen, 2016. "Incorporating Predictability Into Cost Optimization for Ground Delay Programs," Transportation Science, INFORMS, vol. 50(1), pages 132-149, February.
    5. Kim, Myeonghyeon & Bae, Jiheon, 2021. "Modeling the flight departure delay using survival analysis in South Korea," Journal of Air Transport Management, Elsevier, vol. 91(C).
    6. Bojia Ye & Bo Liu & Yong Tian & Lili Wan, 2020. "A Methodology for Predicting Aggregate Flight Departure Delays in Airports Based on Supervised Learning," Sustainability, MDPI, vol. 12(7), pages 1-13, April.
    7. 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.
    8. Chen, Zhenhua & Wang, Yuxuan & Zhou, Lei, 2021. "Predicting weather-induced delays of high-speed rail and aviation in China," Transport Policy, Elsevier, vol. 101(C), pages 1-13.
    9. Sun, Yanshuo & Schonfeld, Paul, 2015. "Stochastic capacity expansion models for airport facilities," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 1-18.

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