Human Systems Integration Perspective on Trajectory-Based Operations: Insights from two SESAR Case Studies

Résumé fourni par la source

Air traffic management (ATM) is at a turning point. The goal is to increase capacity while keeping safety and improving sustainability. At the centre of this change is trajectory-based operations (TBO), a long-planned shift from reactive control to managing flights through shared, precise four-dimensional trajectories and air-ground synchronisation. These two pillars reduce uncertainty and give more options for addressing ATM challenges. TBO depends on digitalisation, which allows trajectory sharing and synchronisation between air and ground. This digital foundation supports higher levels of automation in ATM. Automation here is not only about executing tasks, but deciding the best time, place, and actor (human or system) for each action, based on the best available information. Following the EASA AI roadmap, automation is moving from the role of a simple assistant to that of a teammate, capable of collaborating with human controllers in a shared operational environment. This shift has to be addressed from a Human Systems Integration (HSI) perspective, raising design, procedure, and training challenges. The result is two big changes happening together. Firstly, TBO opens a larger solution space for managing traffic strategically and tactically. Secondly, automation transforms the role of the controller, from tactical operator to strategic orchestrator. This chapter first explains the TBO paradigm, its evolution, and its digital foundations. It then addresses the challenge of integrating automation, comparing approaches and presenting the official European roadmap. A theoretical lens is introduced, using key HSI principles from leading experts. These ideas are applied to two SESAR case studies: a “Digital Assistant” and an “ATC Teammate”. They illustrate the move from human-centred assistance to full human-artificial-agent teamwork. The chapter ends compiling lessons learnt and posing the challenge for the future ahead. This research was conducted within the framework of JARVIS and ATC.TBO projects. JARVIS project has received funding from the SESAR 3 Joint Undertaking (JU) under grant agreement No 101114692 under European Union’s Horizon Europe research and innovation programme. ATC-TBO project has received funding from the SESAR 3 Joint Undertaking (JU) under grant agreement No 101114808 under European Union’s Horizon Europe research and innovation programme. The JU receives support from the European Union’s Horizon Europe research and innovation programme and the SESAR 3 JU members other than the Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or SESAR 3 Joint Undertaking. Neither the European Union nor the granting authority can be held responsible for them.

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