Title: Identifying and modelling correlation between airport weather conditions and additional time in airport arrival sequencing and metering area
Authors: Margarita Bagamanova; Juan José Ramos González; Miquel Àngel Piera Eroles; Jose Manuel Cordero García; Álvaro Rodríguez-Sanz
Addresses: Universitat Autònoma de Barcelona, Carrer de Emprius 2, 08202 Sabadell, Spain ' Universitat Autònoma de Barcelona, Carrer de Emprius 2, 08202 Sabadell, Spain ' Universitat Autònoma de Barcelona, Carrer de Emprius 2, 08202 Sabadell, Spain ' CRIDA A.I.E. (Reference Center for Research, Development and Innovation in ATM), Edificio Allende, Avenida de Aragón 402, 28022 Madrid, Spain ' Universidad Politécnica de Madrid, Plaza Cardenal Cisneros 3, 28040 Madrid, Spain
Abstract: Different uncertainties during operational activities of modern airports can significantly delay some processes and cause chain-effect performance drop on the overall air traffic management (ATM) system. The decision-making process to mitigate the propagation of perturbations through the different airport processes can be improved with the support of a causal model, built with a use of data mining and machine learning techniques. This paper introduces a new approach for modelling causal relationships between various ATM performance indicators, which can be used to predict, by means of simulation techniques, the evolution of airport operations scenarios. The analysis of reachable airport states is a relevant approach to design mitigation mechanisms on those perturbations which drive the system to poor KPIs.
Keywords: ASMA time; holding; inbound traffic; weather impact; Bayesian networks; coloured Petri net; CPN; airport; decision support tool; TMA model.
International Journal of Simulation and Process Modelling, 2019 Vol.14 No.3, pp.213 - 222
Received: 31 Jan 2018
Accepted: 10 Aug 2018
Published online: 16 Jul 2019 *