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A data-driven approach to resilience in air traffic management: case study Barcelona area control centre.

Authors :
Mirkovic, Bojana
Timotic Petkovic, Doroteja
Netjasov, Fedja
Crnogorac, Dusan
Verdonk Gallego, Christian Eduardo
Xia, Chen
Malakis, Stathis
Source :
Cognition, Technology & Work. Sep2024, Vol. 26 Issue 3, p457-485. 29p.
Publication Year :
2024

Abstract

Traditional approaches to safety assessment and management are limited when it comes to complex socio-technical systems, such as air traffic management (ATM). A modelling approach proposed in this paper relies on Resilience Engineering perspective, which is about work-as-done, where safety is one of the targets trading off with other goals. The model provides a description of everyday practices, procedures, strategies, etc. in providing, not only safe, but also efficient ATM system operations. The aim of the model is to help air navigation service providers (ANSPs) that still do not measure and monitor resilience to distinguish between main drivers of traditional safety and drivers of resilience emerging from everyday adaptation to uncertainties. The conceptual layer of the model uses the analogy of lever mechanism to represent the balancing between the demand side (including the uncertainties) and available resources on the supply side that considers air traffic controllers (ATCos), tools and working procedures. The quantitative layer of the model allows identification of periods of resilient behavior (negative demand-capacity imbalances) and thereby steers ANSPs in discovering sources of resilience and finding appropriate resilience indicators to monitor in the future. A data-driven application of the proposed model is shown with the example of Barcelona Area Control Centre – assessment of balancing conditions, analysis of proposed resilience indicators and discussion of the trade-offs. This research focuses on the tactical imbalances that emerge from work-as-done on an everyday basis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14355558
Volume :
26
Issue :
3
Database :
Academic Search Index
Journal :
Cognition, Technology & Work
Publication Type :
Academic Journal
Accession number :
179278494
Full Text :
https://doi.org/10.1007/s10111-024-00770-w