Throughout the project, the team has focused on two complementary topics.
On the one hand, an important effort has been devoted to lay down the foundation of the analysis of air transport from an information processing viewpoint. This included, among others: the analysis of the performance of existing causality and information theory metrics, under different conditions and in real-world data; the validation of these metrics, using synthetic models of air transport; the pre-processing of real delay data, to minimise confounding effects; the development of new techniques for reconstructing networks of delay propagations, based on Deep Learning and other dynamical models; and the simplification of obtained networks, in order to highlight their most salient characteristics. In order to foster the use of these ideas, several open-source libraries have been made available to the community, covering topics like the calculation of information theory metrics, the creation of synthetic time series of delays, and a complete pipeline for the analysis of delay propagation.
On the other hand, these theoretical and computational tools have been deployed to the analysis of multiple air transport systems – chiefly the European one, but also considering US, China, and Africa. Results have highlighted relevant facts about the propagation of delays, both on average and through time; the efficiency of individual airports; the emergence of local patterns of delay propagation centred at specific airports, and how these are consequence of the presence of different types of airlines; and the evolution of the role of airports throughout the day. These have led to the identification of key airports in Europe, i.e. those mostly responsible for the propagation of delays; the quantification of the costs associated to such inefficiencies; and the proposal of operational solutions to mitigate them. Additionally, the project leveraged the widespread impacts of the COVID-19 pandemic, as an instance of a profound and long-lasting perturbation that has disrupted the normal dynamics of the system. Analyses focused on how different systems and airports therein have recovered, the specificities of such recovery, and how changes in dynamics have lingered even years after the peak of the disruption.
