Real-time performance metrics were developed to quantify workload, situational awareness, and manual task performance for use as visual feedback to pilots of aerospace vehicles. Results from prior lunar lander experiments with variable levels of automation were replicated and extended to provide insights for the development of real-time metrics. Increased levels of automation resulted in increased flight performance, lower workload, and increased situational awareness. Automated Speech Recognition (ASR) was employed to detect verbal callouts as a limited measure of subjects' situational awareness. A one-dimensional manual tracking task and simple instructor-model visual feedback scheme was developed. This feedback was indicated to the operator by changing the color of a guidance element on the primary flight display, similar to how a flight instructor points out elements of a display to a student pilot. Experiments showed that for this low-complexity task, visual feedback did not change subject performance, but did increase the subjects' measured workload. Insights gained from these experiments were applied to a Simplified Aid for EVA Rescue (SAFER) inspection task. The effects of variations of an instructor-model performance-feedback strategy on human performance in a novel SAFER inspection task were investigated. Real-time feedback was found to have a statistically significant effect of improving subject performance and decreasing workload in this complicated four degree of freedom manual control task with two secondary tasks.
|School||UNIVERSITY OF CALIFORNIA, DAVIS|
|Subjects||Aerospace engineering; Mechanical engineering|
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