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My Brain Is Out of the Loop: A Neuroergonomic Approach of OOTL Phenomenon

机译:我的大脑走出了循环:ootl现象的神经工艺方法

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The world surrounding us has become increasingly technological. Nowadays, the influence of automation is perceived in each aspect of everyday life and not only in the world of industry. Automation certainly makes some aspects of life easier, faster and safer. Nonetheless, empirical data suggests that traditional automation has many negative performance and safety consequences. Particularly, in cases of automatic equipment failure, human supervisors seemed effectively helpless to diagnose the situation, determine the appropriate solution and retake control, a set of difficulties called the "out-of-the-loop" (OOL) performance problem. Because automation is not powerful enough to handle all abnormalities, this difficulty in "takeover" is a central problem in automation design. The OOL performance problem represents a key challenge for both systems designers and human factor society. After decades of research, this phenomenon remains difficult to grasp and treat and recent tragic accidents remind us the difficulty for human operator to interact with highly automated system. The general objective of our research project is to improve our comprehension of the OOL performance problem. To address this issue, we aim (1) to identify the neuro-functional correlates of the OOL performance problem, (2) to propose design recommendations to optimize human-automation interaction and decrease OOL performance problem occurrence. Behavioral data and brain imaging studies will be used to provide a better understanding of this phenomenon at both physiological and psychological levels.
机译:我们周围的世界变得越来越重要。如今,自动化的影响被认为是日常生活的每个方面,而不仅仅是在工业领域。自动化肯定会使生活更轻松,更快和更安全。尽管如此,经验数据表明,传统的自动化具有许多负面性能和安全后果。特别是,在自动设备故障的情况下,人类监管似乎有效无助诊断情况,确定适当的解决方案和重试控制,一系列困难称为“循环”(OOL)性能问题。由于自动化不足以处理所有异常,因此在“收购”中的这种困难是自动化设计中的核心问题。 OOL性能问题代表了系统设计师和人为因素协会的关键挑战。经过几十年的研究,这种现象仍然很难掌握和治疗,最近的悲惨事故提醒我们人类运营商难以与高度自动化的系统互动。我们研究项目的一般目标是提高我们对OOL性能问题的理解。为了解决这个问题,我们的目标(1)识别ool性能问题的神经功能相关性,(2)提出设计建议,以优化人类自动化互动和减少ool性能问题发生。行为数据和脑成像研究将用于在生理和心理水平方面更好地了解这种现象。

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