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Measuring Self-adaptive UAV Operators' Load-Shedding Strategies under High Workload

机译:在高工作负荷下测量自适应无人机操作员的减载策略

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This article focuses on the experimental identification of changes in human behaviour patterns of UAV-operators guiding multiple UAVs from a helicopter cockpit. These changes are based on self-regulation mechanisms of the operators to adapt to the current task and workload demands. Main objective of the use of these so called self-adaptive strategies is to avoid overload situations, and to retard exceeding capacity limits, to maintain overall acceptable performance as long as possible. Expressed by shedding and deferring tasks of lesser importance, or the relaxation of self-imposed criteria, these strategies lead to an observable change of human behaviour patterns, prior to grave performance decrements. This article describes a laboratory experiment utilising a virtual flight simulator to stimulate operator's workload and observe their mitigation strategies by means of gaze detection and a detailed interaction monitoring. Using the observed behaviour changes in an assistant system as indicator for high workload situations of the operator, it shall be possible to support the operator prior the occurrence of errors.
机译:本文着重于实验性识别从直升机驾驶舱引导多架无人机的无人机操作员的人类行为模式的变化。这些更改基于操作员的自我调节机制,以适应当前的任务和工作量需求。使用这些所谓的自适应策略的主要目标是避免出现过载情况,并延迟超出容量限制,以尽可能长时间地保持总体可接受的性能。通过减少和推迟不太重要的任务或放宽自我施加的标准来表达这些策略,从而在严重降低性能之前导致人类行为模式的可观察到的变化。本文介绍了一个实验室实验,该实验利用虚拟飞行模拟器来刺激操作员的工作量,并通过凝视检测和详细的交互监视来观察其缓解策略。使用在辅助系统中观察到的行为变化作为操作员高工作量情况的指标,应有可能在错误发生之前为操作员提供支持。

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