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Moving Vigilance Out of the Laboratory: Dynamic Scenarios for UAS Operator Vigilance Training

机译:脱离实验室的警惕性:UAS操作员警惕培训的动态情景

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Our technology laden world continues to push the limits of human cognitive performance. Human performers are increasingly expected to assume roles of passive monitors rather than active engagers of technology systems [1]. Active and physical tasks have shifted to more sedentary tasks requiring significant cognitive workload at a rapid pace. Consequently, researchers and academics alike struggle to find a balance between effective user interface, usability, and ergonomic designs that will allow the performer to successfully complete their tasks while sustaining attention in these complex environments. It is no surprise that human error is at the root of tragic mishaps relating to vigilance across a wide range of applications and operational environments [2-4]. Researching vigilance is not new [5-7]. In fact, vigilance has been studied in laboratory settings for nearly seventy years across many conditions and tasks [8]. Traditional laboratory tasks involve static displays with simple image targets presented to individuals over prolonged periods of time. Participants are required to detect rare and temporally spaced targets among abundant "noise" images while sustaining their attention. The results using these vigilance tasks have found evidence of vigilance decrements, increased stress [7], and high cognitive demand [9]. The issue of training the skill to sustain attention has also been addressed [10, 11]. Findings from traditional research show that the most effective way of improving vigilance performance is through providing feedback in the form of knowledge of results [12]. Although the contrived, laboratory-based vigilance tasks can produce and mitigate the vigilance decrement, tasks that directly relate to complex operational environments are severely underrepresented in research. There have only been few researchers that utilize dynamic environments in vigilance research. For example, Szalma et al. [13] developed a video game-based training platform with the goal to extend the traditional vigilance training paradigm to complex, dynamic, and virtual environments that are more representative of visual detection tasks in the real world. Our current research is focused on extending the vigilance training paradigm to operationally relevant areas with the development of a game-based system for training operator attention within unmanned aerial systems (UAS). UAS are an integral part of mission operations within many branches of our military. New developments and improved technology allow extended mission operations of UAS up to, and exceeding 12 h. However, many UAS mishaps are the result of mechanical failures, and an alarming rate - 60.2% - of mishaps have been attributed to operator error [2]. This finding is not surprising, as UAS operations are highly cognitively demanding. Prolonged shiftwork and surveillance missions require sustained attention toward tracking or identifying rare targets, often in visually degraded conditions. This paper discusses current efforts to take the vigilance training paradigm out of the laboratory setting and into operational environments, including our current work in creating game-based training of vigilance for UAS operators. We describe the challenges associated with defining and standardizing targets, developing scenarios, and assessing performance.
机译:我们的技术载货世界继续推动人类认知能力的限制。人类表演者越来越期望假设无源显示器的作用,而不是技术系统[1]的活性接合件。主动和物理的任务已经转移到需要显著的认知工作量以迅猛的速度更久坐的任务。因此,研究人员和学者都颇费周折之间的有效的用户界面,易用性和人体工程学设计的平衡,让表演顺利完成他们的任务,而在这些复杂的环境下保持关注。这是毫不奇怪的是人为错误是在在宽范围的应用和运行环境[2-4]关于警惕悲惨事故的根源。研究警惕性不新[5-7]。事实上,警惕已经研究实验室设置,年近七旬在许多条件和任务[8]。传统的实验室任务涉及超过较长时间呈现给个人简单的图像目标静态展示。参赛者需检测中丰富的“噪音”的图像罕见和时间间隔的目标,同时维持他们的注意力。使用这些警戒任务,结果发现警惕递减的证据,应力增加[7],高认知需求[9]。训练技能,以维持关注的问题也得到解决[10,11]。从传统的研究表明,提高警觉性能的最有效的方法是通过结果的知识[12]的形式提供反馈调查结果。虽然做作,基于实验室的警戒任务可以生产和减轻警惕递减,直接涉及到复杂的作战环境中的任务是研究严重不足。只是有利用在警惕研究动态环境中的一些研究。例如,Szalma等。 [13]开发的一个基于游戏视频培训平台,其目标是传统的警惕训练模式扩展到复杂的,动态的,而且是比较有代表性的现实世界中的视觉检测任务的虚拟环境。我们目前的研究重点是警惕训练模式与游戏为基础的系统的训练无人机系统(UAS)内运营商关注的发展延伸到操作上相关领域。无人机系统任务操作的我军的许多分支中的一个组成部分。新的发展和改进的技术允许无人机系统的扩展任务操作达到和超过12小时。然而,许多事故UAS是机械故障的结果,并以惊人的速度 - 60.2% - 事故的已被归因于操作者错误[2]。这一发现并不令人惊讶,因为UAS操作高度认知苛刻。长期轮班工作制和监视任务需要对跟踪和识别目标罕见,往往在视觉退化的状况持续关注。本文讨论了目前正在努力采取警惕的培训模式走出实验室的设置,进入操作环境,包括我们现在在创造UAS运营商警惕的游戏为基础的培训工作。我们描述定义和规范的目标,发展的情况,并评估性能相关的挑战。

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