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date: 21 February 2020

Abstract and Keywords

This chapter presents a review of adaptive automation (AA) research. The motivation for AA includes previous demonstrations of reduced operator cognitive load, increased operator situation awareness, and improved task performance as compared to static automation or manual control. Design parameters for AA include what functions to automate, how functions are shared between human and machine, when automation is invoked, and who maintains authority over dynamic function allocations (DFAs). Theory and empirical studies on these parameters are reviewed as a basis for design of future systems and identification of research needs. In general, there is a paucity of work on how to transform functions from human to machine, and there have been few comparisons of methods for triggering DFAs. Promising areas of research for advancing AA include hybrid approaches to triggering function allocations and the development of automation etiquette strategies. Additional research is needed to support sensitivity and validity of neuroergonomics methods for AA. Future research is also needed on field implementation.

Keywords: adaptive automation, adaptable automation, human performance, situation awareness, cognitive workload

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