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

• Author(s) / Creator(s)

  • Kim, A.
  • Hansen, M.

• 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. Classical queuing model 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.

• Date created

  2019-11-12

• Subjects / Keywords

  • Airport Runway Operations
  • Empirical Probabilistic Simulation
  • Counterfactual Delay Scenario
  • Aviation Systems Performance Metrics (ASPM) Database
  • New York

• Type of Item

  Article (Draft / Submitted)

• DOI

  https://doi.org/10.7939/r3-25wh-ke16

• License

  Attribution-NonCommercial-NoDerivatives 4.0 International