The impact of air traffic management automation on the human performance of air traffic controllers in aviation law

Hendrikse, Cindy

The impact of air traffic management automation on the human performance of air traffic controllers in aviation law

Thesis / Dissertation

2025

Publisher

University of Cape Town

Department

Department of Private Law

Faculty

Faculty of Law

Abstract

Advancements in communication, navigation, surveillance and air traffic management (CNS/ATM) systems directly impact air traffic controllers (ATCs), who must interact with these technologies within a regulated framework. The hypothesis is that aligning these advancements with their governing international, regional, and national legislation and operational procedures with ATCs in mind will significantly enhance ATCs' performance and trust in these advancements and increase operational safety in a progressively technology-driven environment. Therefore, the research investigated the impact of CNS/ATM advancements on ATCs, the extent to which international, regional and national legislation consider ATCs, and whether the legislation can effectively address the rapid development and growing consequences caused by automation, including artificial intelligence. The study employed a multidisciplinary approach, incorporating a review of human factors research, an analysis of relevant international and European Union aviation law and initiatives, and a comparison of national policies and legislation of the United Kingdom, the Netherlands, and South Africa. Lastly, it included a qualitative survey directed at ATCs to draw from their operational expertise. The human factors literature review highlighted the growing implications of automation, including issues such as complacency, overreliance, distrust in automation, and diminishing manual skills. The legislative analyses unveiled various shortcomings at each level, while the survey revealed that ATCs follow operational procedures regardless of accuracy. Additionally, the survey showed that automation failures significantly increase ATC workload. Lastly, although no participant could indicate how artificial intelligence is currently employed in ATM, most do not trust it nor believe it would be able to control air traffic without any ATC input.