Predictive modeling of inbound demand at major European airports with Poisson and Pre-Scheduled Random Arrivals

Lancia, Carlo and Lulli, Guglielmo (2020) Predictive modeling of inbound demand at major European airports with Poisson and Pre-Scheduled Random Arrivals. European Journal of Operational Research, 280 (1). pp. 179-190. ISSN 0377-2217

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Abstract

This paper presents an exhaustive study of the arrivals process at eight major European airports. Using inbound traffic data, we define, compare, and contrast a data-driven in-homogeneous Poisson and Pre-Scheduled Random Arrivals (PSRA) point process with respect to their ability to predict future demand. As part of this analysis, we show the weaknesses and difficulties of using a non-homogeneous Poisson process to model the arrivals stream. On the other hand, our novel and simple data-driven (PSRA) model captures and predicts the main properties of the typical arrivals stream with good accuracy. These results have important implication for the modeling and simulation-based analyses of inbound traffic and can improve the use of available capacity, thus reducing air traffic delays. In a nutshell, the results lead to the conclusion that, in the European context, the (PSRA) model provides more accurate predictions.