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Experimental Analysis of Behavioral Workload Indicators to Facilitate Adaptive Automation for Fighter-UCAV Interoperability

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Advances in Human Factors in Robots and Unmanned Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 499))

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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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Correspondence to Dennis Mund .

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41958-9

  • Online ISBN: 978-3-319-41959-6

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