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视觉行为测量的变化能否成为驾驶员困倦的良好预测指标?一项实际驾驶测试研究。

Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study.

作者信息

Wang Yonggang, Xin Mengyang, Bai Han, Zhao Yangdong

机构信息

a School of Highway, Chang'an University , Xi'an , Shaanxi , China.

b Department of Transportation & Logistics Engineering , Shandong Jiaotong University , Jinan , Shandong , China.

出版信息

Traffic Inj Prev. 2017 Feb 17;18(2):132-138. doi: 10.1080/15389588.2016.1203425. Epub 2016 Oct 20.

Abstract

OBJECTIVE

The primary purpose of this study was to examine the association between variations in visual behavior measures and subjective sleepiness levels across age groups over time to determine a quantitative method of measuring drivers' sleepiness levels.

METHOD

A total of 128 volunteer drivers in 4 age groups were asked to finish 2-, 3-, and 4-h continuous driving tasks on expressways, during which the driver's fixation, saccade, and blink measures were recorded by an eye-tracking system and the subjective sleepiness level was measured through the Stanford Sleepiness Scale. Two-way repeated measures analysis of variance was then used to examine the change in visual behavior measures across age groups over time and compare the interactive effects of these 2 factors on the dependent visual measures.

RESULTS

Drivers' visual behavior measures and subjective sleepiness levels vary significantly over time but not across age groups. A statistically significant interaction between age group and driving duration was found in drivers' pupil diameter, deviation of search angle, saccade amplitude, blink frequency, blink duration, and closure duration. Additionally, change in a driver's subjective sleepiness level is positively or negatively associated with variation in visual behavior measures, and such relationships can be expressed in regression models for different period of driving duration.

CONCLUSIONS

Driving duration affects drivers' sleepiness significantly, so the amount of continuous driving time should be strictly controlled. Moreover, driving sleepiness can be quantified through the change rate of drivers' visual behavior measures to alert drivers of sleepiness risk and to encourage rest periods. These results provide insight into potential strategies for reducing and preventing traffic accidents and injuries.

摘要

目的

本研究的主要目的是考察不同年龄组视觉行为指标变化与主观困倦水平之间随时间的关联,以确定一种测量驾驶员困倦水平的定量方法。

方法

共有128名来自4个年龄组的志愿者驾驶员被要求在高速公路上完成2小时、3小时和4小时的连续驾驶任务,在此期间,通过眼动追踪系统记录驾驶员的注视、扫视和眨眼指标,并通过斯坦福嗜睡量表测量主观困倦水平。然后采用双向重复测量方差分析来考察不同年龄组视觉行为指标随时间的变化,并比较这两个因素对相关视觉指标的交互作用。

结果

驾驶员的视觉行为指标和主观困倦水平随时间有显著变化,但在不同年龄组之间没有差异。在驾驶员的瞳孔直径、搜索角度偏差、扫视幅度、眨眼频率、眨眼持续时间和闭眼持续时间方面,发现年龄组与驾驶时长之间存在统计学上显著的交互作用。此外,驾驶员主观困倦水平的变化与视觉行为指标的变化呈正相关或负相关,并且这种关系可以在不同驾驶时长阶段的回归模型中表示出来。

结论

驾驶时长对驾驶员的困倦有显著影响,因此应严格控制连续驾驶时间。此外,驾驶困倦可以通过驾驶员视觉行为指标的变化率来量化,以提醒驾驶员困倦风险并鼓励其休息。这些结果为减少和预防交通事故及伤害的潜在策略提供了见解。

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