疲劳预警分级提示下的驾驶行为响应特征

确定疲劳预警提示时机是车载疲劳预警提示技术中的关键和难点，通过驾驶员对预警提示的驾驶行为响应特征来判断提示时机的合理性是解决该问题的新思路. 通过开展在疲劳分级预警提示环境下的驾驶模拟试验，采集驾驶员眼动（眼闭合时间比例）和车道偏移（车道偏移标准差、车道偏移均值、车道越线面积）指标，并通过成对Wilcoxon signed-rank检验，分析不同等级预警提示前后15 s时间内关键驾驶行为指标的差异. 研究结果表明:在设定的疲劳分级规则下，一般疲劳预警提示后，车道偏移标准差均值显著下降0.129 1，车道越线面积均值显著下降8.574 4；在严重疲劳预警提示后，眼闭合时间比例显著下降0.044 9，但车道偏移标准差和车道越线面积均未发生显著改变，驾驶员应该尽快停车休息. 

Driver Behavior Response to Drowsiness Alarming at Different Levels

To identify the timing of drowsiness driving warning is the key issue and a bottleneck of onboard drowsiness driving warning technology. Finding a rationale for warning timing using driver’s driving behavior response feature is an innovation. Therefore, after conducting a driving simulator experiment under the influence of drowsiness alarming, eye movement index, the percentage of eyelid closure (PERCLOS), and vehicle lateral position indexes (standard deviation of lateral position, average of lateral position, area of line exceeding) were recorded. Then, the differences in driving behavior between the pre-warning and post-warning in 15 seconds for each warning were compared using the paired Wilcoxon signed-rank test. The results demonstrated that under the drowsiness classification criterion, after the normal level of drowsiness warning, the mean of the standard deviation of lateral position and the mean of the area of line exceeding significantly dropped down by 0.129 1 and 8.574 4 respectively; after the serious level of drowsiness warning, although the mean of PERCLOS decreased by 0.044 9, the standard deviation of the lateral position and area of line exceeding did not significantly change and that the driver should stop and rest immediately.