TY - JOUR
T1 - The Impact of Automation Conditions on Reliance Dynamics and Decision-Making
AU - Orellana, Carlos Bustamante
AU - Rodriguez, Lucero Rodriguez
AU - Gremillion, Gregory M.
AU - Huang, Lixiao
AU - Demir, Mustafa
AU - Cooke, Nancy
AU - Metcalfe, Jason S.
AU - Amazeen, Polemnia G.
AU - Kang, Yun
N1 - Publisher Copyright:
© 2022 by Human Factors and Ergonomics Society. All rights reserved.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1177/1071181322661477
DO - 10.1177/1071181322661477
M3 - Conference article
AN - SCOPUS:85181091018
SN - 1071-1813
VL - 66
SP - 721
EP - 725
JO - Proceedings of the Human Factors and Ergonomics Society
JF - Proceedings of the Human Factors and Ergonomics Society
IS - 1
T2 - 66th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2022
Y2 - 10 October 2022 through 14 October 2022
ER -