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Drone Fail Me Now: How Drone Failures Afect Trust and Risk-Taking Decisions
KTH, School of Electrical Engineering and Computer Science (EECS).ORCID iD: 0009-0009-8827-5618
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0001-6046-7460
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-2212-4325
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-6158-4818
2024 (English)In: HRI 2024 Companion - Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, Association for Computing Machinery (ACM) , 2024, p. 862-866Conference paper, Published paper (Refereed)
Abstract [en]

So far, research on drone failures has been mostly limited to understanding the technical causes of failures and recovery strategies. In contrast, there is little work looking at how failures of drones are perceived by users. To address this gap, we conduct a real-world study where participants experience drone failures leading to monetary loss whilst navigating a drone over an obstacle course. We tested 46 participants where they experienced both a failure and failure-free (control) interaction. Participants' trust in the drone, their enjoyment of the interaction, perceived control, and future use intentions were all negatively impacted by drone failures. However, risk-taking decisions during the interaction were not affected. These findings suggest that experiencing a failure whilst operating a drone in real-time is detrimental to participants' subjective experience of the interaction.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2024. p. 862-866
Keywords [en]
Drone, Failure, Human-Drone Interaction, Trust, Risk-Taking, UAV
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:kth:diva-344808DOI: 10.1145/3610978.3640609Scopus ID: 2-s2.0-85188131674OAI: oai:DiVA.org:kth-344808DiVA, id: diva2:1847614
Conference
19th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024, Boulder, United States of America, Mar 11 2024 - Mar 15 2024
Note

QC 20240402

Part of ISBN 9798400703232

Available from: 2024-03-28 Created: 2024-03-28 Last updated: 2024-04-02Bibliographically approved

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Rahimzadagan, NoahVahs, MattiLeite, IolandaStower, Rebecca

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