The Impact of Automation Conditions on Reliance Dynamics and Decision-Making

Carlos Bustamante Orellana, Lucero Rodriguez Rodriguez, Gregory M. Gremillion, Lixiao Huang, Mustafa Demir, Nancy Cooke, Jason S. Metcalfe, Polemnia G. Amazeen, Yun Kang

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

The decision process of engaging or disengaging automation has been termed reliance on automation, and it has been widely analyzed as a summary measure of automation usage rather than a dynamic measure. We provide a framework for defining temporal reliance dynamics and apply it to a data-set from a previous study. Our findings show that (1) the higher the reliability of an automated system, the larger the reliance over time; and (2) more workload created by the automation type does not significantly affect the operators’reliance dynamics in high-reliability systems, but it does produce greater reliance in low-reliability systems. Furthermore, on average, operators with low performance make fewer decision changes and prefer to stick to their decision of using automation even if it is not performing well. Operators with high performance, on average, have a higher frequency of decision change, and therefore, their automation usage periods are shorter.

Original languageEnglish (US)
Pages (from-to)721-725
Number of pages5
JournalProceedings of the Human Factors and Ergonomics Society
Volume66
Issue number1
DOIs
StatePublished - 2022
Event66th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2022 - Atlanta, United States
Duration: Oct 10 2022Oct 14 2022

ASJC Scopus subject areas

  • Human Factors and Ergonomics

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