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As air travel tentatively resumes, the move to digitalised ATM infrastructure is seen as critical for making aviation more scalable, economically sustainable, environmentally efficient, predictable and resilient. Against this backdrop, the SESAR Joint Undertaking (SJU) is organising a series of webinars to present the portfolio of SESAR innovations that will make this digital transformation possible.
The rise of new Artificial Intelligence (AI)/Machine Learning technologies provides an opportunity for a fundamental change in the automation landscape. Algorithms based on data-derived knowledge can result in increased ATM performance, safety and resilience but this also comes at the cost of reduced transparency.
This webinar looked at some of the existing theory around AI/machine learning in ATM and explained how we are moving towards higher levels of automation in a safety critical environment. We started with a tangible example of how AI has been able to ensure safety while also increasing runway throughput and resilience for arrival traffic flows. The webinar also explored how we can close the gap between human factors and technology, advancing towards a hybrid human machine collaboration. To complete the picture, the webinar provided the latest update on insights related to trustworthiness and explainability in the safety critical context of ATM.
Higher levels of automation in Time Based Separation during approach
Andy Shand, Head of Queue & Capacity Management Solutions, NATS
Claire Pugh, Wake Optimisation concepts and Analysis Lead, NATS
An overview of Artificial Intelligence methods
Jesus Garcia, Professor Computer Science, Universidad Carlos III de Madrid
The human machine hybrid approach
Marc Baumgartner, Air Traffic Controller, IFATCA
Perspective on Trustworthiness of Artificial Intelligence
Guillaume Soudain, Software Senior Expert, EASA
Moderator: Ruben Flohr, ATM Expert, SESAR Joint Undertaking
Questions raised during the webinar and ...Answers