Validation of Trade-Off in Human–Automation Interaction: An Empirical Study of Contrasting Office Automation Effects on Task Performance and Workload

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dc.contributor.authorLee, Byung Cheol
dc.contributor.authorPark, Jangwoon
dc.contributor.authorJeong, Heejin
dc.contributor.authorPark, Jaehyun
dc.contributor.authorLee, Byung Cheol
dc.contributor.authorPark, Jangwoon
dc.contributor.authorJeong, Heejin
dc.contributor.authorPark, Jaehyun
dc.creator.orcidhttps://orcid.org/0000-0003-4189-0970
dc.creator.orcidhttps://orcid.org/0000-0002-0122-532X
dc.creator.orcidhttps://orcid.org/0000-0002-5264-6941
dc.creator.orcidhttps://orcid.org/0000-0003-4189-0970
dc.creator.orcidhttps://orcid.org/0000-0002-0122-532X
dc.creator.orcidhttps://orcid.org/0000-0002-5264-6941
dc.date.accessioned2020-04-30T19:55:22Z
dc.date.accessioned2020-04-30T19:55:22Z
dc.date.available2020-04-30T19:55:22Z
dc.date.available2020-04-30T19:55:22Z
dc.date.issued2020-02-14
dc.date.issued2020-02-142020-02-14
dc.date.issued2020-02-14
dc.description.abstractAutomation aims to improve the task performance and the safety of human operators. The success of automation can be facilitated with well-designed human–automation interaction (HAI), which includes the consideration of a trade-off between the benefits of reliable automation and the cost of Failed automation. This study evaluated four different types of HAIs in order to validate the automation trade-off, and HAI types were configured by the levels and the statuses of office automation. The levels of automation were determined by information amount (i.e., Low and High), and the statues were decided by automation function (i.e., Routine and Failed). Task performance including task completion time and accuracy and subjective workload of participants were measured in the evaluation of the HAIs. Relatively better task performance (short task completion time and high accuracy) were presented in the High level in Routine automation, while no significant effects of automation level were reported in Failed automation. The subjective workload by the National Aeronautics and Space Administration (NASA) Task Load Index (TLX) showed higher workload in High and Failed automation than Low and Failed automation. The type of sub-functions and the task classification can be estimated as major causes of automation trade-off, and dissimilar results between empirical and subjective measures need to be considered in the design of effective HAI.en_US
dc.description.abstractAutomation aims to improve the task performance and the safety of human operators. The success of automation can be facilitated with well-designed human–automation interaction (HAI), which includes the consideration of a trade-off between the benefits of reliable automation and the cost of Failed automation. This study evaluated four different types of HAIs in order to validate the automation trade-off, and HAI types were configured by the levels and the statuses of office automation. The levels of automation were determined by information amount (i.e., Low and High), and the statues were decided by automation function (i.e., Routine and Failed). Task performance including task completion time and accuracy and subjective workload of participants were measured in the evaluation of the HAIs. Relatively better task performance (short task completion time and high accuracy) were presented in the High level in Routine automation, while no significant effects of automation level were reported in Failed automation. The subjective workload by the National Aeronautics and Space Administration (NASA) Task Load Index (TLX) showed higher workload in High and Failed automation than Low and Failed automation. The type of sub-functions and the task classification can be estimated as major causes of automation trade-off, and dissimilar results between empirical and subjective measures need to be considered in the design of effective HAI.
dc.identifier.citationLee, B.C.; Park, J.; Jeong, H.; Park, J. Validation of Trade-Off in Human–Automation Interaction: An Empirical Study of Contrasting Office Automation Effects on Task Performance and Workload. Appl. Sci. 2020, 10, 1288.en_US
dc.identifier.citationLee, B.C.; Park, J.; Jeong, H.; Park, J. Validation of Trade-Off in Human–Automation Interaction: An Empirical Study of Contrasting Office Automation Effects on Task Performance and Workload. Appl. Sci. 2020, 10, 1288.
dc.identifier.doi10.3390/app10041288
dc.identifier.doi10.3390/app1004128810.3390/app10041288
dc.identifier.doi10.3390/app10041288
dc.identifier.urihttps://hdl.handle.net/1969.6/87834
dc.identifier.urihttps://hdl.handle.net/1969.6/87834https://hdl.handle.net/1969.6/87834
dc.identifier.urihttps://hdl.handle.net/1969.6/87834
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherApplied Sciencesen_US
dc.publisherApplied Sciences
dc.rightsAttribution 3.0 United States*
dc.rightsAttribution 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/
dc.subjecthuman-automation interactionen_US
dc.subjectuser experienceen_US
dc.subjectworkloaden_US
dc.subjecttask performanceen_US
dc.subjectlevel and status of automationen_US
dc.subjectevaluationen_US
dc.subjecthuman-automation interaction
dc.subjectuser experience
dc.subjectworkload
dc.subjecttask performance
dc.subjectlevel and status of automation
dc.subjectevaluation
dc.titleValidation of Trade-Off in Human–Automation Interaction: An Empirical Study of Contrasting Office Automation Effects on Task Performance and Workloaden_US
dc.titleValidation of Trade-Off in Human–Automation Interaction: An Empirical Study of Contrasting Office Automation Effects on Task Performance and Workload
dc.typeArticleen_US
dc.typeArticle

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