Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/129757
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dc.contributor.authorBhaskara, A.-
dc.contributor.authorDuong, L.-
dc.contributor.authorBrooks, J.-
dc.contributor.authorLi, R.-
dc.contributor.authorMcInerney, R.-
dc.contributor.authorSkinner, M.-
dc.contributor.authorPongracic, H.-
dc.contributor.authorLoft, S.-
dc.date.issued2021-
dc.identifier.citationApplied Ergonomics: human factors in technology and society, 2021; 90:1-14-
dc.identifier.issn0003-6870-
dc.identifier.issn1872-9126-
dc.identifier.urihttp://hdl.handle.net/2440/129757-
dc.description.abstractAutomated decision aids can undoubtedly benefit system performance, but have the potential to provide incorrect advice, creating the possibility for automation disuse or misuse. This paper examined the extent to which increased automation transparency could improve the accuracy of automation use in a simulation of unmanned vehicle control. Participants were required to assign the best unmanned vehicle to complete missions. An automated recommender system provided advice but was not always reliable. Three levels of automation transparency were manipulated between-participants. Providing transparency regarding the reasoning underlying automated recommendations improved the accuracy of automation use, with no cost to decision time or subjective workload. Higher transparency in the form of projected decision outcome visualizations led to faster decisions, but less accurate automation use and an automation bias. Implications for the design of transparent interfaces to improve human-autonomy teaming outcomes in time-pressured environments are discussed.-
dc.description.statementofresponsibilityAdella Bhaskara, Lain Duong, James Brook, Ryan Li, Ronan McInerney, Michael Skinner, Helen Pongracic, Shayne Loft-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2020 Elsevier Ltd. All rights reserved.-
dc.subjectAutomation; human-autonomy teaming; unmanned vehicles-
dc.titleEffect of automation transparency in the management of multiple unmanned vehicles-
dc.typeJournal article-
dc.identifier.doi10.1016/j.apergo.2020.103243-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP160100575-
pubs.publication-statusPublished-
Appears in Collections:Aurora harvest 8
Psychology publications

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