Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

Author:

Bailey Nathan R.1,Scerbo Mark W.1,Freeman Frederick G.1,Mikulka Peter J.1,Scott Lorissa A.1

Affiliation:

1. Old Dominion University, Norfolk, Virginia

Abstract

Objective: Two experiments are presented examining adaptive and adaptable methods for invoking automation. Background: Empirical investigations of adaptive automation have focused on methods used to invoke automation or on automation-related performance implications. However, no research has addressed whether performance benefits associated with brain-based systems exceed those in which users have control over task allocations. Method: Participants performed monitoring and resource management tasks as well as a tracking task that shifted between automatic and manual modes. In the first experiment, participants worked with an adaptive system that used their electroencephalographic signals to switch the tracking task between automatic and manual modes. Participants were also divided between high-and low-reliability conditions for the system-monitoring task as well as high- and low-complacency potential. For the second experiment, participants operated an adaptable system that gave them manual control over task allocations. Results: Results indicated increased situation awareness (SA) of gauge instrument settings for individuals high in complacency potential using the adaptive system. In addition, participants who had control over automation performed more poorly on the resource management task and reported higher levels of workload. A comparison between systems also revealed enhanced SA of gauge instrument settings and decreased workload in the adaptive condition. Conclusion: The present results suggest that brain-based adaptive automation systems may enhance perceptual level SA while reducing mental workload relative to systems requiring user-initiated control. Application: Potential applications include automated systems for which operator monitoring performance and high-workload conditions are of concern.

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

Reference53 articles.

1. Psychophysiology and adaptive automation

2. Clamann, M. P. & Kaber, D. B. (2003). Authority in adaptive automation applied to various states of human-machine system information process. In Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting (pp. 543–547). Santa Monica, CA: Human Factors and Ergonomics Society.

3. Clamann, M. P., Wright, M. C. & Kaber, D. B. (2002). Comparison of performance effects of adaptive automation applied to various stages of human-machine system information processing. In Proceedings of the Human Factors and Ergonomics Society 46th Annual Meeting (pp. 342–346). Santa Monica, CA: Human Factors and Ergonomics Society.

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