Description du projet
Des algorithmes améliorés pour une gestion du trafic aérien sûre et fiable
Les solutions d’intelligence artificielle (IA) sont largement utilisées pour étayer la prise de décision dans la gestion du transport aérien. La fiabilité de ces solutions est toutefois remise en question car les décisions qu’elles livrent ne sont pas toujours claires ou compréhensibles par les opérateurs humains. Le projet ARTIMATION, financé par l’UE, introduira des méthodes d’IA innovantes de prévision du trafic aérien et d’optimisation des flux de circulation fondées sur le domaine de l’intelligence artificielle explicable. ARTIMATION cherche à fournir une aide à la décision sûre et fiable, axée sur des modèles d’IA transparents qui comprennent la visualisation, l’explication et la généralisation avec une faculté d’adaptation dans le temps.
Objectif
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.
Champ scientifique
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- social sciencessociologyindustrial relationsautomation
- social sciencessocial geographytransporttransport planningair traffic management
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
722 20 VASTERAAS
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