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Identification of Real-Time Diagnostic Measures of Visual Distraction With an Automatic Eye-Tracking System

机译:利用自动眼动追踪系统识别视力分散的实时诊断措施

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Objective: This study was conducted to identify eye glance measures that are diagnostic of visual distraction. Background: Visual distraction degrades performance, but real-time diagnostic measures have not been identified. Method: In a driving simulator, 14 participants responded to a lead vehicle braking at -2 or -2.7 m/s~2 periodically while reading a varying number of words (6-15 words every 13 s) on peripheral displays (with diagonal eccentricities of 24°, 43°, and 75°). Results: As the number of words and display eccentricity increased, total glance duration and reaction time increased and driving performance suffered. Conclusion: Correlation coefficients between several glance measures and reaction time or performance variables were reliably high, indicating that these glance measures are diagnostic of visual distraction. It is predicted that for every 25% increase in total glance duration, reaction time is increased by 0.39 s and standard deviation of lane position is increased by 0.06 m. Application: Potential applications of this research include assessing visual distraction in real time, delivering advisories to distracted drivers to reorient their attention to driving, and using distraction information to adapt forward collision and lane departure warning systems to enhance system effectiveness.
机译:目的:进行这项研究以鉴定可诊断视力分散的眼睛扫视措施。背景:视力分散会降低性能,但尚未确定实时诊断措施。方法:在驾驶模拟器中,有14位参与者周期性地以-2或-2.7 m / s〜2的速度响应领先的车辆制动,同时在外围显示器(对角偏心)上读取变化数量的单词(每13 s 6-15个单词) 24°,43°和75°)。结果:随着单词数和显示偏心率的增加,总的扫视时间和反应时间增加,并且驾驶性能受到损害。结论:几种扫视措施与反应时间或性能变量之间的相关系数可靠地高,表明这些扫视措施可诊断视力障碍。预计总的扫视时间每增加25%,反应时间将增加0.39 s,车道位置的标准偏差将增加0.06 m。应用:这项研究的潜在应用包括实时评估视觉分心,向分心的驾驶员提供建议以重新定向他们对驾驶的注意力,以及使用分心信息来适应前方碰撞和车道偏离警告系统,以增强系统效率。

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