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TECRA: C2 application of adaptive automation theory

机译:TECRA:C2在自适应自动化理论中的应用

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This paper describes the design and initial positive evaluation of a prototype adaptive automation system to create an enhanced command and control (C2) infrastructure for more effective operation of unmanned vehicles. Our main project objective is to apply recent advances in cognitive engineering and display automation to create Technology for Enhanced Command and Control of Small Robotic Assets (TECRA). The initial goal is an enhanced C2 system for small unmanned aircraft vehicles (SUAVs). Our approach is to use adaptive display technology to improve shared situation awareness between the SUAV Commander and the SUAV Operator, to provide new channels of Commander-Operator communication, and to reduce Commander workload. At the core of our approach is a tri-modal adaptive interface display which involves adaptive information presentation in order to balance workload and to promote effective humansystem performance. This novel design came about as a direct result of field observations during a full-scale military exercise and a cognitive task analysis (CTA) based on these observations. Using the CTA, we designed the basic Commander's adaptive interface format and automated triggering methods. A priori GOMS analysis predicted a 50% decrease in time on task, based on a subset of representative tasks. Data collection to date supports these predictions. Furthermore, feedback from subject matter experts and comparisons between user performance on TECRA versus an existing SUAV platform suggests that TECRA is easier to use, quicker to learn, and provides more capabilities to the user than current systems. These results demonstrate how the TECRA application driven by a cognitive analysis of the Commander's task, by a mission model of the anticipated Commander's needs, and by mission templates and real-time robotic data has been able to validate theories of human-automation interaction in realworld domains such as unmanned aviation and military command and control.
机译:本文介绍了原型自适应自动化系统的设计和初步肯定评估,以创建增强的指挥和控制(C2)基础设施,以更有效地操作无人驾驶车辆。我们的主要项目目标是运用认知工程和显示自动化领域的最新进展来创建增强型小型机器人资产指挥与控制技术(TECRA)。最初的目标是为小型无人机(SUAV)提供增强的C2系统。我们的方法是使用自适应显示技术来提高SUAV指挥官和SUAV操作员之间的共享态势感知,以提供新的指挥官与指挥官之间的通信渠道,并减少指挥官的工作量。我们方法的核心是三模式自适应界面显示,其中涉及自适应信息表示,以平衡工作量并提高有效的人机性能。这项新颖的设计是在全面军事演习中实地观察的直接结果,并基于这些观察进行了认知任务分析(CTA)。使用CTA,我们设计了基本Commander的自适应界面格式和自动触发方法。根据代表任务的子集,先验GOMS分析预测完成任务的时间将减少50%。迄今为止的数据收集支持了这些预测。此外,主题专家的反馈以及TECRA与现有SUAV平台上的用户性能之间的比较表明,与当前系统相比,TECRA更加易于使用,学习更快并且为用户提供了更多功能。这些结果表明,通过指挥官任务的认知分析,预期指挥官需求的任务模型以及任务模板和实时机器人数据驱动的TECRA应用程序已能够验证现实世界中人与自动化交互的理论无人机和军事指挥与控制等领域。

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