With increasing air traffic, the workload of air traffic controllers (ATCOs) and their limited number is again a restricting factor for the evolution of airspace management. Currently, possibilities to apply artificial intelligence for improving the support of ATCOs are widely discussed. By introducing a digital ATCO as a team partner for a human ATCO, we can expand capabilities. It can be trained to manage traffic across various airspace sectors without the limitations imposed by required licenses. This way, shortages of human ATCOs may be absorbed, and flexible assignment to sectors is facilitated with a digital ATCO partner. To be effective, the digital ATCO needs an understanding of current and future traffic situations to share the situation awareness of the human ATCO. The goal is to equip the digital ATCO with a comparable understanding—referred as a “mental model”—of the traffic situation and human actions, thereby improving decision-making and build up adequate trust with humans. In this work, decisive factors of traffic and management for the creation of digital situation awareness are identified and examined for their relevance and applicability for digital ATCOs. Within this study, a data-driven process of building up digital situation awareness including the influencing factors are suggested, and the usability of factors like the airspace complexity for indicating digital situation awareness are proposed. Finally, an example is presented and discussed to showcase our approach with focus on the integration of digital and human ATCOs through shared situation awareness.

Remote air traffic control offers inexpensive and efficient service to multiple airports. Recent research shows that one remote air traffic control officer can safely control up to three low-traffic airports simultaneously. In a multiple remote tower center, airports can be flexibly allocated across air traffic control officers based on prospective traffic loads. The main task of the supervisor in such a center is balancing the workload of each air traffic control officer by allocating airports accordingly. This study analyzes the supervisor's visual attention during interaction with a planning tool for their daily tasks. Five use cases were identified as the main tasks of the supervisor representing a mixture of planned and unplanned events. A mixed methods within-subjects design was used to assess the workload and eye-movement patterns associated with each of these use cases. In total, 15 professional air traffic control officers participated in the study. Workload and eye movement were analyzed independently in relation to the use cases but also in combination with each other. Across all use cases, a small correlation between subjective workload ratings and fixation duration was found, supporting previous findings of fixation duration being associated with information processing. Transitions between areas of interest on the supervisor planning tool provided valuable insights into the layout design of future supervisor planning tools.

While traffic levels are predicted to rise, nearly all European air navigation service providers suffer from staff shortages. In most cases, two air traffic controllers are deployed to control one airspace sector. Enabling the deployment of one controller per sector could be a solution to staff shortage problems. For this Single-Controller Operation (SCO) concept, a demonstrator with integrated support tools based on advanced information technology was developed. These partially automate some controller tasks to allow one controller to work off the same traffic amount as a controller team. The system was tested in a human-in-the-loop real-time simulation under varying traffic loads using a 2 × 2 within-subjects design. The variables assessed include separation minima infringements, exit flight level deviations, instantaneous self-assessment, voice communication, flight distance, and fuel burn. The results show no negative influence on safety, workload, situational awareness, operational efficiency, and environment, with 80% of maximum allowed declared capacity. Thus, SCO has the potential to mitigate staff shortages and raise cost efficiency by 40%. These results showcase the feasibility of the SCO concept under nominal conditions. Assessments with different traffic levels, non-nominal conditions, and an interdependent multi-sector SCO layout are recommended for further investigations.