The Impact of Automation Conditions on Reliance Dynamics and Decision-Making. (September 2022)

• Record Type: Journal Article
• Authors: Orellana, Carlos Bustamante; Rodriguez, Lucero Rodriguez; Gremillion, Gregory M.; Huang, Lixiao; Demir, Mustafa; Cooke, Nancy; Metcalfe, Jason S.; Amazeen, Polemnia G.; Kang, Yun
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 66:Part 1(2022)
• Page Start: 721
• Page End: 725
• Publication Date: 2022-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1071181322661477
• Languages: English
• ISSNs: 1541-9312

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.