In Air Transportation Management the Decision Making Process is already associated with AI. The algorithms are meant to help ATCOs in daily tasks, but they still face acceptability issues. Today’s automation systems with AI/Machine Learning do not provide additional information on top of the Data Processing result to support its explanation, making them not transparent enough. The Decision Making Process is expected to become a “White Box”, giving understandable outcome through an understandable process.
ARTIMATION’s goal is providing a transparent and explainable AI model through visualization, data driven storytelling and immersive analytics. This project will take advantage of human perceptual capabilities to better understand AI algorithm with appropriated data visualization as a support for explainable AI (XAI), exploring in the ATM field the use of immersive analytics to display information
During the first year and a half of the project, we introduced many times the task of Conflict Detection and Resolution. After the Advisory Board
The ARTIMATION project aims to provide Explainability to Artificial Intelligence outcomes through transparent AI models and novel visualisation techniques, following a user-centred approach. The project
On June 9th, ARTIMATION held its 3rd General Assembly meeting. The meeting was held in a hybrid modality: members from the whole Consortium were able
This project has received founding from the SESAR Joint Undertaking grant agreement No. 699381 under European Union’s Horizon 2020 research and innovation programme
Project coordinator
Mälardalen University
Mobyen Uddin Ahmed
mobyen.ahmed@mdh.se
The opinions expressed herein reflect the author’s view only. Under no circumstances shall the SESAR Joint Undertaking be responsible for any use that may be made of the information contained herein.