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'From Decision-Making to Database: Identifying Critical Ground-Based Information in Urban UTM'
Linköping University, Department of Computer and Information Science.
2025 (English)Independent thesis Basic level (degree of Bachelor), 12 credits / 18 HE creditsStudent thesis
Abstract [en]

Urban Air Mobility (UAM) necessitates management methods beyond traditional Air Traffic Management (ATM), to ensure safe and efficient airspace in urban areas. This new approach is termed Unmanned aircraft systems Traffic Management (UTM). However, it has not emerged without challenges. A key issue in this shift is understanding how groundbased events, both scheduled and unscheduled, affect decision-making in UAS Traffic Controllers (UTCOs). This study aims to identify which ground-based constraints are influencing UTM and how information about these constraints should be managed within a future UTM database. To achieve this, data were collected through scenario-centered workshops and semi-structured interviews with air traffic controllers and police representatives. The findings were analyzed through the Joint Control Framework (JCF), particularly the Levels of Autonomy in Cognitive Control (LACC), to understand how ground-based information is integrated into UTM. The results indicate that not all events are equally important for UTCOs. Instead, the informational value depends on context, event type, and operational complexity. Informational requirements for a future database include data about time, location, stakeholders, restrictions, and mission type. This structured data could constitute a foundation to visualize information for UTCOs, and thereby support their decision-making process. The study contributes to the development of socially sustainable UAM by highlighting the need for selective and contextualized data management in UTM systems.

Place, publisher, year, edition, pages
2025. , p. 56
Keywords [en]
Unmanned aircraft systems Traffic Management (UTM), Joint Control Framework (JCF), Naturalistic Decision Making (NDM), Unmanned Areal Vehicle, drones, database, requirement specification, Human-Automation Interaction
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:liu:diva-215978ISRN: LIU-IDA/KOGVET-G--25/027--SEOAI: oai:DiVA.org:liu-215978DiVA, id: diva2:1981525
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Virtual Demonstration
Subject / course
Cognitive science
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Examiners
Available from: 2025-07-04 Created: 2025-07-04 Last updated: 2025-07-04Bibliographically approved

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f26f02dcae531700a9894c29e1cf036c8b39c746c44e3e1da7e57e4498d101c10c9bf8c2fc90d964e7cacf3712a925a1a8eae367df174c369088e15e4ef15719
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Department of Computer and Information Science
Human Computer Interaction

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67891011129 of 553
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf