SESAR: Artificial Intelligence in ATM - Part 1

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 will look at some of the existing theory around AI/machine learning in ATM and will explain how we are moving towards higher levels of automation in a safety critical environment. We will start 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 will also explore how we can close the gap between human factors and technology, advancing towards a hybrid human machine collaboration. To complete the picture, the webinar will provide 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