Development Tendencies in Air Traffic Management
Abstract
This paper investigates the evolution of research themes in Air Traffic Management (ATM) between 2014 and 2024 using keyword co-occurrence analysis. Five dominant clusters—safety and human factors, capacity and airspace efficiency, automation and digitalisation, trajectory-based operations, and sustainability—are identified and interpreted through a socio-technical lens. Beyond describing clusters, the study examines inter-cluster dynamics and situates findings within the policy frameworks of the ICAO Global Air Navigation Plan (GANP) and the European SESAR ATM Master Plan. The use of explicit criteria for keyword normalisation, clustering parameters, and validation metrics enhances methodological transparency. The paper proposes a targeted research agenda for underexplored areas, such as the practical integration of UAS and real-time machine learning in ATC operations. Finally, it outlines practical implications for regulators, ANSPs, technology developers, and training programs, and recommends methodological innovations.
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