Digital technologies and human-machine interaction in air traffic control operations

As global air travel demand rises, airports must manage increasing traffic while maintaining safety standards. Current air traffic management (ATM) systems, particularly within control towers, have limitations that reduce situational awareness by diverting controllers' attention from critical out-of-window views. This research explores the potential of extended reality (XR) technologies to enhance air traffic control (ATC) by delivering spatially relevant information to controllers in real time. The integration of unmanned aerial systems (UAS) into shared airspace further complicates ATM, particularly in low-altitude operations around busy airports. Traditional ATM frameworks and UAS management systems often operate separately, creating risks in congested airspaces where manned and unmanned vehicles coexist. Addressing these challenges, this thesis investigates XR technologies to improve human-machine interfaces (HMI) in ATC, focusing on both tower operations and drone monitoring tasks. Two XR-based systems were developed. The first enhances situational awareness in traditional ATC by enabling controllers to maintain a head-up position through adaptive Augmented Reality (AR) overlays. It integrates multimodal interactions and attention guidance to improve efficiency and reaction times, especially in hazardous conditions. This system was validated through simulated scenarios at Bologna Guglielmo Marconi Airport. The second system facilitates the supervision of both manned and unmanned traffic by overlaying drone-related information and alert cues, allowing seamless monitoring without distracting from primary ATC tasks. This solution, experimentally validated at Toulouse-Blagnac Airport, demonstrated improved operational efficiency, reduced workload, and enhanced situational awareness, though some ergonomic challenges with XR hardware were noted. This thesis highlights the transformative potential of XR in ATC by optimizing controller efficiency and enhancing safety. Future research will focus on overcoming hardware limitations and conducting real-world trials to refine these solutions for practical implementation.