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Advanced Autoplanner 2-a proposed AI supported tool for ATM
LFV, Res & Innovat, Norrkoping, Sweden.
LFV, Res & Innovat, Norrkoping, Sweden.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
LFV, EnRoute Sweden, Norrkoping, Sweden.
2023 (English)In: 2023 IEEE/AIAA 42ND DIGITAL AVIONICS SYSTEMS CONFERENCE, DASC, IEEE , 2023Conference paper, Published paper (Refereed)
Abstract [en]

The project of Advanced Autoplanner 2 (AAP2) focus on work to increase Swedish actors development and knowledge of Artificial Intelligence (AI) for various applications within Air Traffic Management (ATM). The project is a follow up from the previous Advanced Autoplanner (AAP) which focused on the AI technology, without Air Traffic Controller (ATCO) interaction. (Mudhakar et.al. 2021). The AAP2 work was done in collaboration between Luftfartsverket (LFV), Linkoping University (LiU) and Research Institutes of Sweden (RISE).

Place, publisher, year, edition, pages
IEEE , 2023.
Series
IEEE-AIAA Digital Avionics Systems Conference, ISSN 2155-7195, E-ISSN 2155-7209
Keywords [en]
Air Traffic Management; ATM; AI; En-route
National Category
History of Technology
Identifiers
URN: urn:nbn:se:liu:diva-200531DOI: 10.1109/DASC58513.2023.10311200ISI: 001103267600096ISBN: 9798350333572 (electronic)ISBN: 9798350333589 (print)OAI: oai:DiVA.org:liu-200531DiVA, id: diva2:1832752
Conference
IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), Barcelona, SPAIN, oct 01-05, 2023
Available from: 2024-01-30 Created: 2024-01-30 Last updated: 2024-01-30

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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Language
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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