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Usage of more trans...
Usage of more transparent and explainable conflict resolution algorithm : Air traffic controller feedback
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- Hurter, C. (författare)
- Ecole Nationale de l'aviation Civile, 7 Avenue Edouard Belin, Toulouse, France
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- Degas, A. (författare)
- Ecole Nationale de l'aviation Civile, 7 Avenue Edouard Belin, Toulouse, France
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- Guibert, A. (författare)
- Ecole Nationale de l'aviation Civile, 7 Avenue Edouard Belin, Toulouse, France
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- Durand, N. (författare)
- Ecole Nationale de l'aviation Civile, 7 Avenue Edouard Belin, Toulouse, France
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- Ferreira, A. (författare)
- Deep Blue s.r.l., Via Manin 53, 00185 Rome, Italy
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- Cavagnetto, N. (författare)
- Deep Blue s.r.l., Via Manin 53, 00185 Rome, Italy
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- Islam, Mir Riyanul, Doctoral Student, 1991- (författare)
- Mälardalens universitet,Akademin för innovation, design och teknik
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- Barua, Shaibal (författare)
- Mälardalens universitet,Inbyggda system
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- Ahmed, Mobyen Uddin, Dr, 1976- (författare)
- Mälardalens universitet,Inbyggda system
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- Begum, Shahina, 1977- (författare)
- Mälardalens universitet,Inbyggda system
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- Bonelli, S. (författare)
- Deep Blue s.r.l., Via Manin 53, 00185 Rome, Italy
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- Cartocci, G. (författare)
- Deep Blue s.r.l., Via Manin 53, 00185 Rome, Italy
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- Flumeri, G. D. (författare)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, Rome, Italy
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- Borghini, G. (författare)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, Rome, Italy
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- Babiloni, F. (författare)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, Rome, Italy
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- Aricó, P. (författare)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, Rome, Italy
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Ecole Nationale de l'aviation Civile, 7 Avenue Edouard Belin, Toulouse, France Deep Blue sr.l., Via Manin 53, 00185 Rome, Italy (creator_code:org_t)
- Elsevier B.V. 2022
- 2022
- Engelska.
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Ingår i: Transportation Research Procedia. - : Elsevier B.V.. - 2352-1457 .- 2352-1465. ; 66:C, s. 270-278
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
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- Recently, Artificial intelligence (AI) algorithms have received 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. To address this challenge related to transparency of the automated system in the ATM domain, we investigated AI methods in predicting air transportation traffic conflict 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 for air traffic controllers. In this paper, we report our research directions and our findings to support better decision making with AI algorithms with extended transparency.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
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Hurter, C.
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Degas, A.
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Guibert, A.
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Durand, N.
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Ferreira, A.
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Cavagnetto, N.
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Islam, Mir Riyan ...
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Barua, Shaibal
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Ahmed, Mobyen Ud ...
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Begum, Shahina, ...
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Bonelli, S.
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Cartocci, G.
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Flumeri, G. D.
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Borghini, G.
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Babiloni, F.
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Aricó, P.
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Mälardalens universitet