New centrality and causality metrics assessing air traffic network interactions. (June 2020)

• Record Type: Journal Article
• Authors: Mazzarisi, Piero; Zaoli, Silvia; Lillo, Fabrizio; Delgado, Luis; Gurtner, Gérald
• Is Part Of: Journal of air transport management. Volume 85(2020)
• Publication Date: 2020-06
• Subjects: Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2020.101801
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: In ATM systems, the massive number of interacting entities makes it difficult to identify critical elements and paths of disturbance propagation, as well as to predict the system-wide effects that innovations might have. To this end, suitable metrics are required to assess the role of the interconnections between the elements and complex network science provides several network metrics to evaluate the network functioning. Here we focus on centrality and causality metrics measuring, respectively, the importance of a node and the propagation of disturbances along links. By investigating a dataset of US flights, we show that existing centrality and causality metrics are not suited to characterise the effect of delays in the system. We then propose generalisations of such metrics that we prove suited to ATM applications. Specifically, the new centrality is able to account for the temporal and multi-layer structure of ATM network, while the new causality metric focuses on the propagation of extreme events along the system. Highlights: Need of network tools to characterise systemic effects of innovations in ATM networks. Existing centrality and causality metrics are not suitable, we introduce new ones. New centrality metric accounts for temporal multiplex structure of ATM networks. New causality metric individuates channels of propagation of extreme disturbances.