Date of Award
Master of Science
Department of Systems Engineering and Management
Michael E. Miller, PhD.
It is often useful to understand the impact of an artificial teammate upon human workload in human-machine teams. Levels of Autonomy (LoA) differentiate systems based on control authority. Unfortunately, human workload is not necessarily correlated with LoA. An alternate classification framework, designated the Level of Human Control Abstraction (LHCA), is proposed. LHCA differentiates system states based on the control and monitoring tasks performed and the level of decisions made by humans. The framework defines five levels, designed to differentiate between system states based upon anticipated levels of human attention. This presentation will summarize the framework and demonstrate its application.
DTIC Accession Number
Johnson, Clifford D., "A Framework for Analyzing and Discussing Level of Human Control Abstraction" (2017). Theses and Dissertations. 1656.