Abstract
This work describes the impact of artificial assistant on the operator’s performance which is applied to correct the operator’s actions in case of unsafe or ineffective behavior. In order for assistive control to be effective a method to evaluate and predict operator performance should be applied. This paper presents a model of operator activity based on histograms of the distribution of reaction times to particular stimuli. The model is then applied to the task of monitoring operator activity in a controlled environment, designed to emulate certain actions performed by an aircraft pilot. For each subject, an individual behavioral portrait is made. Then, performance changes under high operational load conditions and impact of assistive control are evaluated.
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Acknowledgments
This work is supported by the Russian Ministry of Science and Higher Education, project no. 2.955.2017/4.6.
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Kopeliovich, M., Kozubenko, E., Kashcheev, M., Shaposhnikov, D., Petrushan, M. (2020). Impact of Assistive Control on Operator Behavior Under High Operational Load. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V., Tiumentsev, Y. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research III. NEUROINFORMATICS 2019. Studies in Computational Intelligence, vol 856. Springer, Cham. https://doi.org/10.1007/978-3-030-30425-6_5
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DOI: https://doi.org/10.1007/978-3-030-30425-6_5
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