Probabilistic Modeling of Runway Interdeparture Times

T HE Erlang distribution has been used to model the runway service process in queuing models of air traffic operations [1–3] since its use was first proposed by Hengsbach and Odoni [4]. It has been shown to offer certain computational advantages because it can be viewed as a sum of exponential distributions. However, there have been few prior efforts to validate Erlang distribution assumptions using operational data, and even those have only been performed informally with aggregate or low-fidelity data [5]. This Note uses high-fidelity surface surveillance data to model the probability distributions of runway service times and examine the goodness of fit of the Erlang distribution. For this, probabilistic models for the runway service times are derived from empirical departure throughput distributions and empirical departure time distributions. The results are compared in terms of bias, goodness of fit, and computational advantages. The analysis has implications to both the modeling of airport operations and to the estimation of airport capacities.