The necessary introduction of artificial intelligence into air traffic management brings many advantages, but also challenges. AI agents are joining air traffic control teams as separate members, capable of processing vast amounts of data and providing insights and support to their human team members. In these interactions, human air traffic controllers understand the machines - how they operate, what their mission is, how best to use their strenghts, and how to mitigate their limitations. Machines, for now, lack the understanding of what the humans are doing, thus not allowing them to fulfill their role and full potential in human-machine teams.
Building on the results of a previous SESAR project, which demonstrated that an AI system is capable of using air traffic information to build an understanding of the traffic situation (i.e. artificial situational awareness), project AWARE aims to broaden that awareness by including human controllers' goals and intent. It would do so by tracking visual attention, but improved by including other inputs such as how the controller interacts with their work station. By also forming a complete picture of the traffic situation, the system would also be able to detect if the human controller is experiencing loss of situational awareness and assist them in bringing them back "into the loop". This would allow the system to provide better, human-centric support to ATCOs. By modifiying its outputs to their needs, it could improve their performance and reduce workload in complex traffic situations. ATCOs would be able to modify how support from the AI system manifests, or more precisely which actions the asisstant completes. It is also of interest to see if the benefits of using an AI assistant may be transferred to other roles within air traffic management, beyond en-route air traffic control.
