Predictive modeling of inbound demand at major European airports with Poisson and Pre-Scheduled Random Arrivals
| Autor: | Carlo Lancia, Guglielmo Lulli |
|---|---|
| Přispěvatelé: | Lancia, C, Lulli, G |
| Rok vydání: | 2020 |
| Předmět: |
Information Systems and Management
General Computer Science Operations research Computer science 0211 other engineering and technologies Transportation Context (language use) Poisson process 02 engineering and technology Management Science and Operations Research Poisson distribution Industrial and Manufacturing Engineering Point process Modeling and simulation symbols.namesake Data-driven modeling 0502 economics and business 050210 logistics & transportation 021103 operations research 05 social sciences Process (computing) Contrast (statistics) Air traffic control Demand prediction Modeling and Simulation Air traffic symbols |
| Zdroj: | European Journal of Operational Research. 280:179-190 |
| ISSN: | 0377-2217 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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