生理疲劳和心理疲劳对车辆驾驶的影响对比北大核心CSCD

针对现有疲劳驾驶预警和干预技术研究鲜有对生理疲劳和心理疲劳进行区分考虑的问题,为对比这两类典型疲劳态对驾驶员车辆驾驶过程的事故倾向影响,分别从性别、年龄和驾龄的角度分3批次共招募90位驾驶员进行状态诱发和驾驶实验。结果表明:尽管生理疲劳和心理疲劳都会如传统研究所述导致各驾驶员的驾驶违规倾向增加和驾驶能力降低,但是二者对于各类别驾驶员的驾驶影响程度和规律存在差异甚至迥异。研究疲劳驾驶相关问题时有必要首先判断驾驶员是生理疲劳还是心理疲劳,这是一个被普遍忽视而又可能影响研究结论准确性和有效性的重要因素。     

基于驾驶操作行为的驾驶员疲劳状态识别模型研究

以驾驶疲劳状态监测为研究对象,介绍现有几种疲劳检测方法及其优缺点,提出把驾驶行为操作和驾驶员生理指标相结合建立疲劳识别模型的思想。通过大量模拟器驾驶实验,建立驾驶操作和驾驶员生理指标之间的关系模型,并运用最小二乘法对数学模型进行了参数识别。利用驾驶员生理指标能较好判别驾驶员状态特性的特点,找出驾驶操作行为和驾驶状态之间的关系。研究结果有助于建立驾驶操作行为和驾驶员疲劳状态之间的关系模型。     

道路交通环境中驾驶疲劳的生成模型研究

为预防由驾驶疲劳引起的交通事故,有必要研究在道路、交通和环境的综合影响下驾驶疲劳的生成机理。基于生理、心理学中的经典理论,借鉴国内外相关的研究成果,采用理论推理的方法对驾驶疲劳生成过程中驾驶员唤醒水平的变化规律及其影响因素进行分析。在此基础上建立了驾驶疲劳的生成模型,并将模型应用于工程实际。通过驾驶员唤醒水平的变化,指出驾驶疲劳的生成时刻,及其对驾驶时间的规定和道路、景观设计的影响。该模型以唤醒水平为核心,描述驾驶疲劳生成过程中驾驶员唤醒水平的变化规律,强调道路交通环境对驾驶员唤醒水平的影响。     

基于生理信号的驾驶疲劳综合指标试验研究

研究驾驶过程中随着疲劳的产生驾驶员生理信号的变化规律,提取反映驾驶疲劳程度的综合指标。采用驾驶模拟器对20名被试进行驾驶模拟试验,用MP150多导生理仪实时采集并记录驾驶员在60 min驾驶任务过程中的心电信号、脑电信号、肌肉电阻信号、皮肤温度信号和呼吸频率信号。运用R软件对数据进行线性回归分析,对比一般回归分析,逐步线性回归分析克服了一般回归分析许多变量不显著的缺点,得到了最优的驾驶综合指标方程,确定了与各项指标相关的驾驶疲劳评价综合指标,并通过3名被试模拟驾驶试验验证了综合指标作为评价驾驶疲劳的有效性。     

疲劳驾驶交通事故的特点分析与预防

疲劳驾驶引发的道路交通事故导致了严重的人身伤亡和财产损失。本文从心理和生理两方面分析了疲劳形成机理,对我国2006年因疲劳驾驶导致的交通事故进行了疲劳事故特点分析,并根据统计分析结果制定针对性的预防措施,从而减少疲劳驾驶交通事故的发生率。     

高速公路疲劳驾驶交通事故的控制

针对我国高速公路疲劳驾驶交通事故频发的现状,结合高速公路行车特点,从驾驶员高速行车的生理心理及高速公路行车环境等方面分析高速公路疲劳驾车交通事故原因。根据交通心理学、安全人机学等原理,提出驾驶者自身控制、运输单位内部管理、宣传和舆论、家庭教导、交通部门服务性诱导、交通管理部门的执法和管理等各个方面提出高速公路疲劳驾驶交通事故的控制措施。     

基于计算机视觉的驾驶疲劳识别方法的研究

汽车驾驶员疲劳驾驶是引发交通事故的重要原因之一,许多国家在进行疲劳报警器的研究。在介绍和比较多种驾驶疲劳测评方法的基础上,阐述PERCLOS评价驾驶疲劳的机理,并与其他几种方法进行对比,以证明其优越性。设计一套驾驶员疲劳监控系统,应用图像差分的方法,灰度直方图、直方图均衡化等图像分析手段,定位和识别驾驶员眼睛睁开与闭合的变化过程,统计出眼睛闭合时间来确定疲劳程度,并通过利用MATLAB得以实现。给出了一种基于PERCLOS的驾驶员疲劳识别的新方法。     

长时间单调模拟驾驶对疲劳的影响研究

通过模拟驾驶实验,综合评估长时间驾驶以及单调环境对驾驶员疲劳程度的影响是笔者研究的主要课题内容。借助于在模拟驾驶座舱上,4个健康样本分别参加高速公路(单调环境)和一般公路(非单调环境)的两组驾驶仿真实验,每组测试均持续两小时,一共进行10次实验。实验过程中,样本的操控数据(车速和方向盘转角)、反应时间、心电信号、主观疲劳状况等都同步记录并保存。实验结果表明长时间驾驶对操控能力、反应时间、心率、主观疲劳都有显著性影响(p<0.050),单调环境(高速公路)和非单调环境(一般公路)相比,车速方差区别显著,而尽管被试在高速公路的单调环境下驾驶后主观感觉更疲劳一些,但反应时间、心率等因素并没有显著性差异。     

生理节律对北京市出租车司机驾驶疲劳的影响

为探索生理节律对出租车司机驾驶疲劳的影响,选取具有代表性的15名北京市出租车司机,使用闪光融合频率计、动作稳定器、视觉反应时测试仪3种实验仪器,分实验组和空白组对出租车司机驾驶状态分时段进行多次测试,在数据统计分析基础上对出租车司机疲劳规律进行研究.结果 表明:出租车司机驾驶疲劳主要表现为困倦、身体不适以及倦怠3个方面.8:00司机疲劳程度最低,13:00疲劳特征关键点;7:00 ～13:00疲劳主要因素是生理节律,其显著特征是困倦,而工作方式对疲劳的影响相对较小;13:00 ～ 20:00疲劳的主要因素是工作方式和生理节律,其显著特征是困倦、身体不适和倦怠.     

车载驾驶员疲劳驾驶预警与控制系统研究

为了识别与安全控制疲劳危险驾驶行为,有效预防与减少因疲劳危险驾驶导致的交通事故,基于疲劳检测分级、预警与自动智能控制技术,开发出车载驾驶员疲劳驾驶实时监测预警与控制系统。首先基于PERCLO方法,构建驾驶员疲劳检测与分级模型;然后根据所输出的驾驶员疲劳等级信息,提出疲劳驾驶三级预警原理,及其预警实现方式;最后以疲劳预警信息为基础,形成基于驾驶员不同疲劳等级预警的安全控制技术,并对处于深度疲劳的危险驾驶行为,构建自动智能紧急控制停车系统,重点阐述系统的地形匹配、智能控制,以及自动驾驶与停车三大核心技术,并提出相应的系统硬件构成,为系统工程应用提供理论与技术支持。     

A pre/post evaluation of fatigue,stress and vigilance amongst commercially licensed truck drivers performing a prolonged driving task

Purpose. The main purpose of this research study was to evaluate changes in fatigue, stress and vigilance amongst commercially licensed truck drivers involved in a prolonged driving task. The secondary purpose was to determine whether a new ergonomic seat could help reduce both physical and cognitive fatigue during a prolonged driving task. Two different truck seats were evaluated: an industrial standard seat and a new truck seat prototype. Methods. Twenty male truck drivers were recruited to attend two testing sessions, on two separate days, with each session randomized for seat design. During each session, participants performed two 10-min simulated driving tasks. Between simulated sessions, participants drove a long-haul truck for 90 min. Fatigue and stress were quantified using a series of questionnaires whereas vigilance was measured using a standardized computer test. Results. Seat interactions had a significant effect on fatigue patterns. Conclusion. The new ergonomic seat design holds potential in improving road safety and vehicle accidents due to fatigue-related accidents.     

轮班制度对于地铁司机疲劳的影响

立足于轮班工作模式,阐述轮班制度对司机疲劳产生与积累的影响。介绍疲劳指数方法和池田公式的理论基础及模型构架,基于北京地铁13号线现行轮班表,分别应用上述两种研究方法进行地铁轮班司机疲劳程度的分析。两种方法的评估结果显著相关,均说明13号线现行轮班表的制定会导致司机疲劳的产生,存在安全运营风险。应用上述方法可实现对司机疲劳程度的非接触式测量,避免对司机驾驶作业的干扰,同时为地铁运营公司的安全管理人员制定合理的轮班方案,建立全面、量化的动态管理措施,提高行车安全保障提供了科学依据。     

疲劳驾驶交通事故的严重程度影响因素分析

为探究和定量分析疲劳驾驶交通事故严重程度的影响因素,以广东省1 370条疲劳驾驶事故数据为基础,对比分析不同年份、时间段以及年龄段的疲劳驾驶交通事故特征;以交通事故严重程度为因变量,将其分为严重事故和非严重事故,从驾驶员年龄、驾龄、车辆类型等17个初步选择的自变量中筛选对疲劳驾驶交通事故严重程度具有显著影响的因素;采用二元Logistic回归模型分别对全体数据和不同道路类型下的数据建立疲劳驾驶交通事故严重程度预测模型,并对模型进行参数估计和检验。研究结果表明：模型拟合度良好,准确性高;对疲劳驾驶交通事故严重程度具有显著影响的因素有年龄、人员类型、车辆类型、道路类型、道路线形和能见度;车辆类型和道路线形是影响城市道路交通事故严重程度的重要因素,能见度是影响1,2级及其他更低级道路交通事故严重程度的重要因素。     

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices. Method: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.     

真实条件下长时间作业的驾驶安全性影响研究

为研究长时间单调驾驶对驾驶员疲劳、嗜睡、反应时间和驾驶速度的确切影响,以合作企业3系重卡为操作对象进行了一组真实驾驶条件试验。在自愿的基础上随机地从合作企业物流公司选择12名经验丰富的驾驶员作为试验的驾驶员样本。试验采用主观评分方法记录试验者的嗜睡和疲劳状况,所有数据分析基于统计学软件PASW Statistic 18.0。试验结果表明长时间单调驾驶会导致驾驶员疲劳和嗜睡,而疲劳和嗜睡在一定的程度上会导致驾驶速度的加快,却没有导致驾驶员反应时间的显著变化。在持续驾驶3 h之后驾驶员的疲劳和驾驶绩效发生了明显劣化,故从安全的角度考虑应以2~3 h为界合理安排司机的作业负荷和绩效考评。     

基于驾驶员模型参数辨识的疲劳驾驶研究

提出一种利用驾驶员模型反演方法来进行驾驶员疲劳诊断研究的新方法。首先利用预瞄神经网络建立适应于复杂路况条件下的驾驶员-汽车-道路闭环模型,然后定义特定行驶轨迹内理论数据与试验数据的近似度为目标函数,将驾驶员参数的反演问题转化为多目标优化问题,采用基于实数编码混沌变异量子遗传算法的优化方法,获得全局最优解。试验中采用脑电和主观疲劳心理评测结合的方法确定被试者的疲劳状况。在每种疲劳状况下对驾驶员参数进行辨识,对结果进行统计分析表明,在考虑到车型、道路曲率等因素条件下驾驶员参数分布与驾驶员的疲劳状况有很强的相关性。     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.