Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Trustworthy UAV relationships: applying the schema action world taxonomy to UAVsand UAV swarm operations

Parnell, Katie J., Fischer, Joel E., Clark, Jediah R., Bodenmann, Adrian, Galvez Trigo, Maria Jose ORCID: https://orcid.org/0000-0001-6492-0955, Brito, Mario P., Divband Soorati, Mohammad, Plant, Katherine L. and Ramchurn, Sarvapali D. 2022. Trustworthy UAV relationships: applying the schema action world taxonomy to UAVsand UAV swarm operations. International Journal of Human-Computer Interaction 10.1080/10447318.2022.2108961

[thumbnail of Trustworthy UAV Relationships Applying the Schema Action World Taxonomy to UAVs and UAV Swarm Operations.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

Human Factors play a significant role in the development and integration of avionic systems to ensure that they are trusted and can be used effectively. As Unoccupied Aerial Vehicle (UAV) technology becomes increasingly important to the aviation domain this holds true. This study aims to gain an understanding of UAV operators’ trust requirements when piloting UAVs by utilising a popular aviation interview methodology (Schema World Action Research Method), in combination with key questions on trust identified from the literature. Interviews were conducted with six UAV operators, with a range of experience. This identified the importance of past experience to trust and the expectations that operators hold. Recommendations are made that target training to inform experience, in addition to the equipment, procedures and organisational standards that can aid in developing trustworthy systems. The methodology that was developed shows promise for capturing trust within human-automation interactions.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Publisher: Taylor and Francis Group
ISSN: 1044-7318
Funders: UKRI Trustworthy Autonomous Systems Hub
Date of First Compliant Deposit: 11 April 2023
Date of Acceptance: 29 July 2022
Last Modified: 29 Jun 2024 11:17
URI: https://orca.cardiff.ac.uk/id/eprint/158549

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics