Abstract
In this article, we present an experimental study investigating the operationalization of behavioral indicators of pilots’ mental workload in a military manned-unmanned teaming scenario. For the identification of such behavioral workload indicators, we conducted an explorative experimental campaign. We chose an air-to-ground low-level flight mission with multiple target engagements. To further increase the task load of the pilots, we introduced an embedded secondary task, i.e. the classification of target pictures delivered by remote UCAVs. This is a typical task, which we expect in future manned-unmanned teaming setups. The examination of the subjective ratings shows that high individual workload states were achieved. In these high workload situations, the subjects used various behavioral adaptations to keep a high performance level while regulating their subjective workload. As these behavioral adaptations occur prior to grave performance decrements, we consider to use behavioral changes as indicator for high workload and as trigger for adaptive support.
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References
Hawkins, K.: “www.army.mil,” U.S.Army, October, 6th 2014 (Online). Available: http://www.army.mil/article/135412/Unmanned_aircraft_soar_with_new_capabilities_for_Apache_teaming/. Accessed 25 Feb 2016
Baxter, J., Horn, G., Leivers, D.: Fly-by-agent: controlling a pool of UAVs via a multi-Agent System. In: Knowledge-Based Systems (2008)
Parasuraman, R.: Adaptive automation for human-robot teaming in future command and control systems. In: Army Research Lab Aberdeen Proving Ground Md Human Research and Engineering Directorate (2007)
Honecker, F.: Human-System Interaction Analysis for Military Pilot Activity and Mental Workload Determination, Hong Kong (2015)
Sperandio, J.-C.: Variation of operator’s strategies and regulating effects on workload. Ergonomics 14(5), 571 (1971)
Veltman, J., Jansen, C.: The role of operator state assessment in adaptive automation. In: TNO-DV2 2005 A245 (2006)
Sperandio, J.-C.: The regulation of working methods as a function of workload among air traffic controllers. Ergonomics 21(3), 195 (1978)
Schulte, A., Donath, D.: Measuring self-adaptive UAV operators’ load-shedding strategies under high workload. In: Engineering Psychology and Cognitive Ergonomics, Heidelberg (2011)
Canham, L.: Operability testing of command, control & communications in computers and intelligence (C41) systems. In: Handbook of Human Factors Testing and Evaluation, p. 433 (2001)
Hart, S., Staveland, L.: Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. Adv. Psychol. 52, 139 (1988)
Jones, R.M., et al.: Using cognitive workload analysis to predict and mitigate workload for training simulation. Procedia Manuf. 3, 5777 (2015)
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Mund, D., Heilemann, F., Reich, F., Denk, E., Donath, D., Schulte, A. (2017). Experimental Analysis of Behavioral Workload Indicators to Facilitate Adaptive Automation for Fighter-UCAV Interoperability. In: Savage-Knepshield, P., Chen, J. (eds) Advances in Human Factors in Robots and Unmanned Systems. Advances in Intelligent Systems and Computing, vol 499. Springer, Cham. https://doi.org/10.1007/978-3-319-41959-6_20
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DOI: https://doi.org/10.1007/978-3-319-41959-6_20
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