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dc.contributor.advisorde Weck, Olivier
dc.contributor.advisorFazel-Zarandi, Mohammad
dc.contributor.authorChevallier, Juliette
dc.contributor.otherMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.
dc.date.accessioned2021-12-22T17:25:05Z
dc.date.available2021-12-22T17:25:05Z
dc.date.copyright2021
dc.date.issued2021
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/138771
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, June, 2021
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Department of SLOAN, June, 2021
dc.descriptionCataloged from the official PDF of thesis.
dc.descriptionIncludes bibliographical references (pages 258-261).
dc.description.abstractAutonomous air vehicles are rapidly gaining interest within the aviation industry with novel business cases such as urban air mobility, package delivery, and more. However, these increasingly autonomous systems come with increasingly numerous and complex inputs that software must handle. This limitless set of inputs must ensure that autonomous system decisions will translate to operations that are safe for the general public. This thesis contributes to knowledge by introducing an ontology and framework, with supporting analyses, to align individuals before beginning research and product development efforts in autonomous vehicles. This framework and the supporting ontology and analyses seek to provide a quantitative, repeatable method for describing the increase of operational uncertainty with the increase in automation for a UAS.en_US
dc.description.statementofresponsibilityby Juliette Chevallier.
dc.format.extent261 pages
dc.language.isoenen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
dc.source.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectManagement.
dc.subjectAeronautics and Astronautics.
dc.titleEnabling Autonomy in Commercial Aviation: An Ontology and Framework for Automating Unmanned Aircraft Systems (UAS)en_US
dc.typeThesisen_US
dc.description.degreeS.M.
dc.description.degreeM.B.A.
dc.description.collectionM.B.A. Massachusetts Institute of Technology, Sloan School of Management
dc.description.collectionS.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
mit.thesis.degreeMaster
mit.thesis.departmentSloan
mit.thesis.departmentAero


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