a Transportation Research Center of Beijing University of Technology , Beijing , P.R. China.
Traffic Inj Prev. 2014;15(8):801-8. doi: 10.1080/15389588.2014.881996.
The purpose of this study was to analyze the effects of fatigue driving and drunk driving on drivers' physical characteristics; to analyze the differences in drivers' physical characteristics affected by different kinds of fatigue; and to compare the differences in the effects of the 2 driving states, fatigue driving and drunk driving.
Twenty-five participants' physical characteristics were collected under 5 controlled situations: normal, tired driving, drowsy driving, drowsiness + tired driving, and drunk driving. In this article, fatigue driving refers to tiredness and drowsiness and includes 3 situations: tired driving, drowsy driving, and drowsiness + tired driving. The drivers' physical characteristics were measured in terms of 9 parameters: systolic blood pressure (SBP), heart rate (HR), eyesight, dynamic visual acuity (DVA), time for dark adaption (TDA), reaction time to sound (RTS), reaction time to light (RTL), deviation of depth perception (DDP), and time deviation of speed anticipation (TDSA). They were analyzed using analysis of variance (ANOVA) with repeated measures. Binary logistical regression analysis was used to explain the relationship between drivers' physical characteristics and the two driving states.
Most of the drivers' physical characteristic parameters were found to be significantly different under the influence of different situations. Four indicators are significantly affected by fatigue driving during deep fatigue (in decreasing order of influence): HR, RTL, SBP and RTS. HR and RTL are significant in the logistical regression model of the drowsiness + tired driving situation and normal situations. Six indicators of the drivers' physical characteristics are significantly affected by drunk driving (in decreasing order of influence): SBP, RTL, DDP, eyesight, RTS, and TDSA. SBP and DDP have a significant effect in the logistical regression model of the drunk driving situation and the normal situation.
Both fatigue driving and drunk driving are found to impair drivers' physical characteristics. However, their impacts on the parameters SBP, HR, eyesight, and TDSA are different. A driver's physical characteristics will be impaired more seriously when he continues driving while drowsy, compared to driving under normal situation. These findings contribute to the current research on identifying drivers' driving state and quantifying the effects of fatigue driving and drunk driving on driving ability and driving behavior.
本研究旨在分析疲劳驾驶和酒后驾驶对驾驶员生理特征的影响；分析不同类型疲劳对驾驶员生理特征的影响差异；并比较这两种驾驶状态（疲劳驾驶和酒后驾驶）的影响差异。
在 5 种控制条件下采集 25 名参与者的生理特征：正常、疲劳驾驶、瞌睡驾驶、疲劳+瞌睡驾驶和酒后驾驶。本文中的疲劳驾驶是指疲劳和瞌睡，包括 3 种情况：疲劳驾驶、瞌睡驾驶和疲劳+瞌睡驾驶。驾驶员的生理特征通过 9 个参数进行测量：收缩压（SBP）、心率（HR）、视力、动态视觉敏锐度（DVA）、暗适应时间（TDA）、声音反应时间（RTS）、光反应时间（RTL）、深度知觉偏差（DDP）和速度预期时间偏差（TDSA）。采用重复测量的方差分析（ANOVA）进行分析。采用二元逻辑回归分析解释驾驶员生理特征与两种驾驶状态之间的关系。
在不同情况下，大多数驾驶员的生理特征参数均有显著差异。在深度疲劳下，有 4 个指标受到疲劳驾驶的显著影响（影响程度依次降低）：HR、RTL、SBP 和 RTS。在瞌睡+疲劳驾驶和正常情况下的逻辑回归模型中，HR 和 RTL 是显著的。在酒后驾驶中，有 6 个驾驶员生理特征指标受到显著影响（影响程度依次降低）：SBP、RTL、DDP、视力、RTS 和 TDSA。在酒后驾驶和正常情况下的逻辑回归模型中，SBP 和 DDP 有显著影响。
疲劳驾驶和酒后驾驶都会损害驾驶员的生理特征。然而，它们对 SBP、HR、视力和 TDSA 等参数的影响是不同的。与正常情况下相比，当驾驶员在瞌睡时继续驾驶时，其生理特征会受到更严重的损害。这些发现有助于当前对驾驶员驾驶状态的识别和对疲劳驾驶和酒后驾驶对驾驶能力和驾驶行为影响的量化研究。
