UTM regulatory concerns with machine learning and artificial intelligence

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dc.contributor.authorRyan, Richard
dc.contributor.authorAl-Rubaye, Saba
dc.contributor.authorBraithwaite, Graham
dc.date.accessioned2022-11-04T11:22:28Z
dc.date.available2022-11-04T11:22:28Z
dc.date.issued2022-10-31
dc.description.abstractArtificial intelligence (AI) and machine learning will have a significant impact on the application of drones and the integration of universal/unmanned traffic management (UTM) that relate to unmanned operations in urban environments at very low-level airspace. Artificial intelligence will necessitate high levels of automation and act as an enabler with respect to the integration of unmanned and manned aviation and will ultimately enable safe operations with respect to high numbers of drones utilising the same airspace, and more specifically with respect to detect and avoid capability. AI is going to be heavily developed and utilised by organisations that certify as U-space service providers (USSP’s) when providing a service to Unmanned Aerial Systems (UAS) Operators. The equipment utilised by UAS Operators will to some extent already benefit from AI, but the level of automation is currently constrained by regulation. A legal framework must exist, as AI will not only have a significant impact upon existing laws but will ensure a framework that facilitates safety and the fundamental rights of citizens and businesses with respect to AI. The EU has published a proposed law, namely the Artificial Intelligence Act as permitted under Article 114 of the Treaty on the Functioning of the European Union (TFEU).en_UK
dc.identifier.citationRyan R, Al-Rubaye S, Braithwaite G. (2022) UTM regulatory concerns with machine learning and artificial intelligence. In: 2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC), Portsmouth, 18-22 September 2022, Virginia, USAen_UK
dc.identifier.eisbn978-1-6654-8607-1
dc.identifier.eissn2155-7209
dc.identifier.isbn978-1-6654-8608-8
dc.identifier.issn2155-7195
dc.identifier.urihttps://doi.org/10.1109/DASC55683.2022.9925869
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18655
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectArtificial intelligenceen_UK
dc.subjectU-space service providers (USSP’s)en_UK
dc.subjectUniversal Traffic Management (UTM)en_UK
dc.subjectUnmanned Aerial Systems (UAS)en_UK
dc.subjectautomationen_UK
dc.subjectregulationen_UK
dc.subjectlegal frameworken_UK
dc.subjecthuman machine teamsen_UK
dc.subjecthuman in the loopen_UK
dc.subjecthuman on the loopen_UK
dc.subjecthuman outside the loopen_UK
dc.subjectEU AI Acten_UK
dc.subjectmachine learning (ML)en_UK
dc.titleUTM regulatory concerns with machine learning and artificial intelligenceen_UK
dc.typeConference paperen_UK

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