Colloquium: Sjoerd van Rooijen (C&O)

18 januari 2019 14:00 - Locatie: Lecture Hall D, Faculty of Aerospace Engineering, Kluyverweg 1, Delft.

Personalized Automation for Air Traffic Control using Convolutional Neural Networks.

In the upcoming years, airspace capacity is mainly limited by air traffic controller workload, requiring the
introduction of automation to assist controllers with conflict detection and resolution. However, acceptance is
considered to be one of the main obstacles to introduce novel automation. Individual-sensitive automation has
been proposed to increase acceptance by adapting to different controller strategies. This research evaluates
how personalized automation for air traffic control can be achieved using convolutional neural networks. A
human-in- the-loop experiment is devised to generate a dataset consisting of conflict resolutions with
corresponding velocity obstacle images as learning feature. Results show that the trained models can
reasonably predict command type, direction and directional value. Furthermore, a correlation is found between
a controller consistency metric and achieved prediction performance. Finally, the individual-sensitive models
performed significantly better than general group-based models, confirming the strategy heterogeneity of the
population, which is a critical assumption for personalized automation.