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TRANSPARENT ARTIFICIAL INTELLIGENCE AND AUTOMATION TO AIR TRAFFIC MANAGEMENT SYSTEMS

Project description

Improved algorithms for safety and reliability in air traffic management

Among other fields, artificial intelligence (AI) solutions are widely used to support decision-making tasks in air transportation management. However, their reliability is under question because the decisions provided are not always clear or understandable by human operators. The EU-funded ARTIMATION project will introduce innovative AI methods to predict air transportation traffic and to optimise traffic flows based on the domain of explainable artificial intelligence. ARTIMATION aims to ensure safe and dependable decision support, focusing on transparent AI models that include visualisation, explanation and generalisation with adaptability over time.

Objective

Recently, Artificial intelligence (AI) algorithms have shown increasable interest in various application domains including in Air Transportation Management (ATM). Different AI in particular Machine Learning (ML) algorithms are used to provide decision support in autonomous decision-making tasks in the ATM domain e.g. predicting air transportation traffic and optimizing traffic flows. However, most of the time these automated systems are not accepted or trusted by the intended users as the decisions provided by AI are often opaque, non-intuitive and not understandable by human operators. Safety is the major pillar to air traffic management, and no black box process can be inserted in a decision-making process when human life is involved. In order to address this challenge related to transparency of the automated system in the ATM domain, ARTIMATION focuses on investigating AI methods in predicting air transportation traffic and optimizing traffic flows based on the domain of Explainable Artificial Intelligence (XAI). Here, AI models’ explainability in terms of understanding a decision i.e. post hoc interpretability and understanding how the model works i.e. transparency can be provided in the air traffic management. In predicting air transportation traffic and optimizing traffic flows systems, ARTIMATION will provide a proof-of-concept of transparent AI models that includes visualization, explanation, generalization with adaptability over time to ensure safe and reliable decision support.

Coordinator

MALARDALENS UNIVERSITET
Net EU contribution
€ 350 000,00
Address
HOGSKOLEPLAN 1
721 23 VASTERAAS
Sweden

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Region
Östra Sverige Östra Mellansverige Västmanlands län
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 350 000,00

Participants (3)