Uncertainty management at the airport transit view
Rodríguez Sanz, Álvaro (Universidad Politécnica de Madrid. Departamento de Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos)
Gómez Comendador, Fernando (Universidad Politécnica de Madrid. Departamento de Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos)
Arnaldo Valdés, Rosa (Universidad Politécnica de Madrid. Departamento de Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos)
Cordero García, Jose Manuel (Universidad Politécnica de Madrid. Departamento de Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos)
Bagamanova, Margarita (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)

Date:	2018
Abstract:	Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the Airport Transit View framework, focusing on the airspace/airside integrated operations. In this analysis, we use a dynamic spatial boundary associated with the Extended Terminal Manoeuvring Area concept. Aircraft operations are characterised by different temporal milestones, which arise from the combination of a Business Process Model for the aircraft flow and the Airport Collaborative Decision-Making methodology. Relationships between factors influencing aircraft processes are evaluated to create a probabilistic graphical model, using a Bayesian network approach. This model manages uncertainty and increases predictability, hence improving the system's robustness. The methodology is validated through a case study at the Adolfo Suárez Madrid-Barajas Airport, through the collection of nearly 34,000 turnaround operations. We present several lessons learned regarding delay propagation, time saturation, uncertainty precursors and system recovery. The contribution of the paper is two-fold: it presents a novel methodological approach for tackling uncertainty when linking inbound and outbound flights and it also provides insight on the interdependencies among factors driving performance.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Airport operations ; System congestion ; Delay propagation ; Business Process Modelling ; Bayesian networks
Published in:	Aerospace, Vol. 5 (2018) , p. 1-31, ISSN 2226-4310

DOI: 10.3390/aerospace5020059

31 p, 9.6 MB

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