首页> 美国卫生研究院文献>Frontiers in Human Neuroscience >Brain–Computer Interface-Based Adaptive Automation to Prevent Out-Of-The-Loop Phenomenon in Air Traffic Controllers Dealing With Highly Automated Systems
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Brain–Computer Interface-Based Adaptive Automation to Prevent Out-Of-The-Loop Phenomenon in Air Traffic Controllers Dealing With Highly Automated Systems

机译:基于脑-计算机接口的自适应自动化可防止空中交通管制员处理高度自动化系统时出现超限现象

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摘要

Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo’s mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called “Vigilance and Attention Controller”, a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human–machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA.
机译:空中交通管理自动化水平的提高被视为提高服务性能以满足预期的未来需求的一种措施。预计这将为操作员带来新的角色:他将主要监视高度自动化的系统,并且很少干预。因此,空中交通管制员(ATCos)通常将以监督或控制模式而不是直接运行模式工作。但是,事实证明,扮演这种角色的操作员如何受到人为绩效问题(称为OOTL)现象的影响,这种现象包括注意力不足,处境意识丧失和技能下降。在自适应自动化(AA)中,即在能够根据操作需求将操作任务分配给机器或操作员的系统中,已经确定了针对该现象的对策。在这种情况下,心理生理措施已成为一种强大的工具,可以对ATCo的心理状态进行可靠,不干扰和实时的评估,以用作基于AA的系统的控制逻辑。在本文中,我们介绍了所谓的“警惕和注意控制器”,它是一种基于脑电图(EEG)和眼动追踪(ET)技术的系统,旨在实时评估ATCo处理人的警惕水平。高度自动化的人机界面,并使用此方法来适应界面本身的自动化水平。该系统已在14个专业ATCo上进行了测试,它们执行两种高度现实的方案,一种禁用系统,另一种启用系统。结果证实:(i)长时间的高自动化任务会引起警觉性下降和与OOTL相关的现象; (ii)脑电图措施对这类精神障碍敏感; (iii)机管局能够通过让ATCo更多地参与手术任务来抵消这种负面影响。脑电图和ET测度以及性能和主观测度证实了该结果,为AA的潜在应用和相关益处提供了清晰的例子。

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