Robustness of Air Transportation as Complex Networks:Systematic Review of 15 Years of Research and Outlook into the Future

Abstract

Air transportation systems are an important part of the critical infrastructure in our connected world. Accordingly, a better understanding and improvements in the resilience of the overall air transportation system are essential to the well-functioning of our society and overall sustainability of human beings. In the literature, network science is increasingly used to better understand the resilience dynamics of air transportation. Given the wide application of tools for network science and the importance of designing resilient air transportation systems, a rich body of studies has emerged in recent years. This review paper synthesizes the related literature that has been published throughout the last 15 years regarding the robustness of air transportation systems. The contributions of this work consist of two major elements. The first part provides a comprehensive discussion and cross-comparison of the reported results. We cover several major topics, including node importance identification, failure versus attack profiles, recovery and improvement techniques, and networks of networks approaches. The second part of this paper complements the review of aggregated findings by elaborating on a future agenda for robust air transportation research. Our survey-style overview hopefully contributes toward a better understanding of the state of the art in this research area, and, in turn, to the improvement of future air transportation resilience and sustainability.

Modeling Resilience of Air Traffic Management Systems Based on Complex Networks

“…In the opposite direction, however, scale-free networks are particularly vulnerable to attacks targeting the most central and influential nodes in the network. Sun and Wandelt (2021) reinforce these ideas by analyzing the different impacts of attacks, concluding that targeted attacks are more harmful to ATM systems than random failures.…”

A novel resilience analysis methodology for airport networks system from the perspective of different epidemic prevention and control policy responses

“…Domaneschi et al (2016) proposed a recovery index based on time and system characteristics to analyze the overall system, and a general recovery function that can be applied to a variety of recovery modes [28]. In 2020, the performance of the aviation network was significantly reduced; therefore, studies on the shape of the system recovery function for the post-epidemic period have used a U-shape or L-shape [29]SUN_x_2021_airports. Kou (2019) proposed a post-earthquake bridge recovery model based on sigmoid functions, which can be obtained in various functional forms such as positive and negative exponentials by adjusting the coefficients [30].…”

On the ramifications of airspace bans in aero-political conflicts: Towards a country importance ranking

“…Variations of this model concerns the applications on cities, regions, countries and weighted versions, e.g., using the number of flights or number of passengers as link weights. Several studies in the literature dissect the impact of random failures and targeted attack on the well-functioning of the network in different spatial extensions, see Sun and Wandelt (2021) for a recent review on air transportation network robustness. Cardillo et al (2013) model the European aviation system as an interdependent multi-layer network and compares the robustness of the single-plex representation with the proposed, more realistic multiplex one, finding that the latter strongly affects the robustness of the network.…”