Comparison of Adaptive, Adaptable, and Hybrid Automation for Surveillance Task Completion in a Multi-Task Environment. (September 2018) - Ruff, Heath; Calhoun, Gloria; Frost, Elizabeth; Behymer, Kyle; Bartik, Jessica
Increasing applications of automation in system designs raise issues on how to achieve an ideal balance of automation with human interaction for optimal operator situation awareness and performance. This experiment examined four automation control schemes applied to surveillance tasks performed in a multi-task simulation environment. Participants completed trials with four level of automation (LOA) control schemes: fixed, performance-based adaptive, adaptable (participant controls LOA), and hybrid (adaptive and adaptable). Results showed that task accuracy was better when participants controlled LOA. Participants also preferred adaptable automation.