Adaptive automation (AA) is the dynamic allocation of control of system functions to a human operator and/or computer over time with the purpose of optimizing overall system performance. This paper describes the ability of human operators to interact with AA applied to various stages of complex systems information processing, defined in a model of human-automation interaction. In the study, 40 participants operated a simulated air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making). AA also appeared superior to completely manual control. These findings would be useful for designing automated systems for air traffic controller information processing tasks.
Abstract