New centrality and causality metrics assessing air traffic network interactions

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 the authors 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, the authors show that existing centrality and causality metrics are not suited to characterise the effect of delays in the system. The authors then propose generalisations of such metrics that they 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.


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  • Accession Number: 01739440
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 18 2020 11:28AM