Automation, Individual Differences, Attention, Human-Machine Interaction
As system automation increases and evolves, the intervention of the supervising operator becomes ever less frequent but ever more crucial. The adaptive automation approach is one in which control of tasks dynamically shifts between humans and machines, being an alternative to traditional static allocation in which task control is assigned during system design and subsequently remains unchanged during operations. It is proposed that adaptive allocation should adjust to the individual operators' characteristics in order to improve performance, avoid errors, and enhance safety. The roles of three individual difference variables relevant to adaptive automation are described: attentional control, desirability of control, and trait anxiety. It was hypothesized that these traits contribute to the level of performance for target detection tasks for different levels of difficulty as well as preferences for different levels of automation. The operators' level of attentional control was inversely proportional to automation level preferences, although few objective performance changes were observed. The effects of sensory modality were also assessed, and auditory signal detection was superior to visual signal detection. As a result, the following implications have been proposed: operators generally preferred either low or high automation while neglecting the intermediary level; preferences and needs for automation may not be congruent; and there may be a conservative response bias associated with high attentional control, notably in the auditory modality.
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Doctor of Philosophy (Ph.D.)
College of Arts and Sciences
Length of Campus-only Access
Doctoral Dissertation (Open Access)
Thropp, Jennifer, "Individual Preferences In The Use Of Automation" (2006). Electronic Theses and Dissertations. 1103.