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Effect of automation transparency in the management of multiple unmanned vehicles.
Bhaskara, Adella; Duong, Lain; Brooks, James; Li, Ryan; McInerney, Ronan; Skinner, Michael; Pongracic, Helen; Loft, Shayne.
Afiliación
  • Bhaskara A; Defence Science and Technology Group, 506 Lorimer Street, Fishermans Bend, VIC, 3207, Australia; The University of Adelaide, SA, 5005, Australia. Electronic address: adella.bhaskara@dst.defence.gov.au.
  • Duong L; The University of Western Australia, 35 Stirling Highway, Perth WA, 6009, Australia.
  • Brooks J; Defence Science and Technology Group, 506 Lorimer Street, Fishermans Bend, VIC, 3207, Australia.
  • Li R; The University of Western Australia, 35 Stirling Highway, Perth WA, 6009, Australia.
  • McInerney R; Defence Science and Technology Group, 506 Lorimer Street, Fishermans Bend, VIC, 3207, Australia.
  • Skinner M; Defence Science and Technology Group, 506 Lorimer Street, Fishermans Bend, VIC, 3207, Australia.
  • Pongracic H; Defence Science and Technology Group, 506 Lorimer Street, Fishermans Bend, VIC, 3207, Australia.
  • Loft S; The University of Western Australia, 35 Stirling Highway, Perth WA, 6009, Australia. Electronic address: shayne.loft@uwa.edu.au.
Appl Ergon ; 90: 103243, 2021 Jan.
Article en En | MEDLINE | ID: mdl-32919121
Automated 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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis y Desempeño de Tareas / Sistemas Hombre-Máquina Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Appl Ergon Año: 2021 Tipo del documento: Article Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis y Desempeño de Tareas / Sistemas Hombre-Máquina Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Appl Ergon Año: 2021 Tipo del documento: Article Pais de publicación: Reino Unido