Department of Psychology, Clemson University, Clemson, SC, USA.
Department of Psychology, Clemson University, Clemson, SC, USA.
Accid Anal Prev. 2015 Jul;80:117-24. doi: 10.1016/j.aap.2015.04.007. Epub 2015 Apr 17.
Driving while sleepy is a serious contributor to automobile accidents. Previous research has shown that drowsy drivers produce systematic errors (variability) in vehicle behavior which are detectable using vehicle monitoring technology. The current study developed a new methodological approach using a vehicle heading difference metric to detect drowsy driving more effectively than other more commonly used methods. Twenty participants completed a driving scenario as well as several measures of fatigue in five testing sessions across a night of sleep deprivation. Each simulated highway driving session lasted 20 min, and was analyzed for lateral lane position variability and vehicle heading difference variability with two statistical methods. Fatigue measures monitored reaction time, attention, and oculomotor movement. The results showed that examining lane heading difference using the absolute value of the raw data detected driving variability better across the night than other statistical models. The results from the fatigue measures indicated an increase in reaction time and response lapses, as well as a decrease in oculomotor reactivity across the night. These results suggest that in fatigued drivers the statistical model using the absolute value of lane heading could be an improved metric for drowsy driving detection that could accurately detect detriments in driving ability at lower levels of fatigue.
困倦驾驶是导致汽车事故的一个重要原因。先前的研究表明，困倦的司机在车辆行为上会产生系统误差（可变性），这些误差可以通过车辆监控技术检测到。目前的研究使用车辆航向差度量标准开发了一种新的方法学方法，与其他更常用的方法相比，该方法能够更有效地检测困倦驾驶。20 名参与者在剥夺一夜睡眠的五次测试中完成了驾驶场景以及几项疲劳测量。每个模拟高速公路驾驶时段持续 20 分钟，并使用两种统计方法分析横向车道位置变异性和车辆航向差变异性。疲劳测量监测了反应时间、注意力和眼球运动。结果表明，使用原始数据的绝对值检查车道航向差可以在整个夜间更好地检测到驾驶可变性，优于其他统计模型。疲劳测量的结果表明，反应时间和反应失误增加，眼球运动反应性降低。这些结果表明，在疲劳的司机中，使用车道航向绝对值的统计模型可能是一种改进的困倦驾驶检测指标，可以在较低的疲劳水平下准确检测驾驶能力的下降。
