主成分分析法和德尔菲结合法的影响驾驶行为指标构建

为了构建影响驾驶行为的指标,统计了影响驾驶行为的41项因素。针对这些因素,制作了调查问卷,并对各个行业的120名驾驶员发放问卷。对收回的有效问卷结果进行统计,并采用主成分分析法和模糊德尔菲与灰色德尔菲法结合两种方法对问卷结果进行分析。主成分分析与德尔菲结合法都能有效地将驾驶员观点定量化,进而得到对驾驶员行为相对影响较大的指标。比较两种方法的分析结果,运用交叉法得到了19个主要影响驾驶行为的指标。     

营运驾驶员驾驶事故影响因素仿真研究

解决营运驾驶员驾驶事故频发的不安全行为问题,基于复杂适应系统（CAS）理论和多主体建模与仿真（ABMS）方法,构建营运驾驶员驾驶事故模型。通过调节车辆状况、管理者管理监督水平、营运驾驶员情绪状态、安全教育水平、驾驶经验和环境综合条件等因素,运用NetLogo仿真平台分析安全管理水平、营运驾驶员安全责任意识、心理负荷水平对驾驶事故的影响。研究表明:营运驾驶员驾驶事故的发生系统是一种典型的CAS,营运驾驶员驾驶事故是三大主体属性和行为环境交互的结果,且交互作用程度不同。因此,运输企业要考虑多种因素,采取相应的措施来降低营运驾驶员驾驶事故的发生。     

驾驶汽车生理素质的训练（一）

目前全世界范围每年约有60多万人死于道路交通事故中，通过对事故的分析和交通安全工程师对人车安全系统的研究，发现驾驶人的生理素质对事故的发生有密切联系。因此，要想安全驾驶一生，就必须了解驾驶员生理方面的知识，掌握一些克服驾驶员生理对安全不利因素的方法。影响驾驶安全的生理因素主要有驾驶员的视觉特性、听觉特性、人体感觉特性、驾驶疲劳特性以及酒后驾车等对安全行车的影响。     

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。     

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。     

生理疲劳和心理疲劳对车辆驾驶的影响对比

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。     

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。     

交通事故致因中的人为因素分析

为改善交通安全状况,减少交通事故,从最主要的因素——人为因素出发,分析其影响。导致事故发生的主要原因是:驾驶员处理交通事件的能力(包括新手、老年、酒精、药物、疲劳、压力等),驾驶员在驾驶时采取冒险行为(包括不正确使用安全带、超速、犯罪、自杀等)。结果表明:新手驾驶、饮酒驾驶、疲劳驾驶、不正确使用安全带驾驶等仍是影响交通安全的主要因素。     

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。     

城市道路养护作业对驾驶员安全驾驶的影响

从市政养护的满意度、驾驶员行为调查以及城市交通标志识别等方面展开调查,发现私家车、公交车和出租车对道路养护作业的满意度存在显著差异,3类车型的驾驶员在安全驾驶行为上也存在明显差异。私家车驾驶员的驾驶失误行为明显高于出租车和公交车驾驶员。违规越多的驾驶员,其驾驶攻击性行为越强。同时道路养护中的常见标志对不同类型的驾驶员产生不同的信息量。私家车驾驶员对于交通标志的理解程度明显高于出租车和公交车驾驶员。     

女性驾驶人特性与行为机制研究现状及展望

为系统地认识女性驾驶人的驾驶特性,分析其驾驶行为,从女性驾驶人交通事故数据统计、致因和心理、生理、“药驾”等因素,梳理国内外女性驾驶人驾驶特性及行为机制的研究成果,总结主流研究角度、方法和内容,并展望其未来研究趋势。对文献的梳理和分析表明:导致女性驾驶人交通事故的因素主要包括人格、认知等心理特征和视觉能力、应激反应等生理特征,同时“药驾”也影响着驾驶特性与行为。剖析了女性驾驶人特性及行为机制研究目前存在的不足之处,对未来的研究提出了建议。并针对女性驾驶人群体在各种道路交通环境中开展有效的模拟驾驶培训和教育,进而全面提升中国女性驾驶人的交通安全水平。     

Experiences from dual-country drivers: Driving safely in China and the US

This study explored the international experience of driving in two countries from the perspectives of drivers. It highlighted the differences in driving experiences between China and the US from people who have driven in both countries. A qualitative research approach utilizing focus group discussions was conducted in China and the US. The pros and cons, strengths and weaknesses of the transportation systems in the two countries were discussed. Car accidents or near misses due to differences between the two countries were explored. Advice for people who want to drive in these two countries as foreign visitors was discussed. Results showed that there are strengths and weaknesses in both countries in their driving systems. Both countries could benefit from exploring the traffic and roadway system of the other.     

Traffic climate and driver behaviors: The moderating role of driving skills in Turkey and China

Introduction: While road traffic accidents and fatalities are a worldwide problem, the rates of road traffic accidents and fatalities show differences among countries. Similarly, driver behaviors, traffic climate, and their relationships also show differences among countries. The aim of the current study is to investigate the moderating effect of driving skills on the relationship between traffic climate and driver behaviors by country. (Turkey and China). Method: There were 294 Turkish drivers and 292 Chinese drivers, and they completed the Traffic Climate Scale, the Driving Skills Inventory, and the Driver Behavior Questionnaire. The moderated moderation analyses were conducted with Hayes PROCESS tool on SPSS. Results: The results showed that safety skills moderated the relationship between internal requirements and violations both in Turkey and China. Safety skills also moderated the relationship between internal requirements and errors only in China and the relationship between functionality and violations in Turkey. Perceptual-motor skills moderated the relationships between external affective demands and errors, and also the relationship between internal requirements and positive driver behaviors in Turkey. It can be inferred that driving skills has different influences on traffic climate-driver behaviors relationship in different cultures and there might be cultural differences in the evaluation of drivers’ own driving skills. Practical Applications: Among driving skills, safety skills have a more critical role to increase road safety by decreasing number of violations. Interventions to increase safety skills of drivers might be promising for road safety.     

Modeling drivers’ reaction when being tailgated: A Random Forests Method

Background: Tailgating is a common aggressive driving behavior that has been identified as one of the leading causes of rear-end crashes. Previous studies have explored the behavior of tailgating drivers and have reported effective solutions to decrease the amount or prevalence of tailgating. This paper tries to fill the research gap by focusing on understanding highway tailgating scenarios and examining the leading vehicles’ reaction using existing naturalistic driving data. Method: A total of 1,255 tailgating events were identified by using the one-second time headway threshold criterion. Four types of reactions from the leading vehicles were identified, including changing lanes, slowing down, speeding up, and making no response. A Random Forests algorithm was employed in this study to predict the leading vehicle’s reaction based on corresponding factors including driver, vehicle, and environmental variables. Results: The analysis of the tailgating scenarios and associated factors showed that male drivers were more frequently involved in tailgating events than female drivers and that tailgating was more prevalent under sunny weather and in daytime conditions. Changing lanes was the most prevalent reaction from the leading vehicle during tailgating, which accounted for more than half of the total events. The results of Random Forests showed that mean time headway, duration of tailgating, and minimum time headway were three main factors, which had the greatest impact on the leading vehicle drivers’ reaction. It was found that in 95% of the events, leading vehicles would change lanes when being tailgated for two minutes or longer. Practical Applications: Results of this study can help to better understand the behavior and decision making of drivers. This understanding can be used in designing countermeasures or assistance systems to reduce tailgating behavior and related negative safety consequences.     

In-vehicle workload assessment: effects of traffic situations and cellular telephone use

PROBLEM: Assessment of drivers' on-road workload is an important traffic safety consideration. This study was conducted to examine the effects of cellular phone communication on driving performance, with particular emphasis on variations in task demand in different traffic situations. METHOD: Twelve participants were asked to drive on urban roads and motorways with or without concomitant mathematical-addition tests relayed via cellular phone. Measurements included task and driving performance, physiological responses, and compensatory behavior. RESULTS: Analysis of task performance revealed that mean response time was markedly increased (11.9%) for driving on urban roads compared to motorways. The mean driving speed only decreased 5.8% in the presence of phone tasks in comparison to normal driving without distractions. In addition, overall physiological workload increased through compensatory behavior in response to the phone tasks. CONCLUSIONS: Driving with phone use in different traffic environments induced measurable variations in driver workload. IMPACT ON INDUSTRY: When faced with heavy traffic, a greater safety margin is typically adopted, with more lowered driving speed and restricted phone use, and it can be assumed that there is a general trade-off between tasks to preserve driving safety.     

Predictability of clinical assessments for driving performance

PROBLEM: As the number of older drivers grows, it is increasingly important to accurately identify at-risk drivers. This study tested clinical assessments predictive of real-time driving performance. METHOD: Selected assessment tools considered important in the identification of at-risk older drivers represented the domains of vision, cognition, motor performance, and driving knowledge. Participants were administered the battery of assessments followed by an on-road test. A univariate analysis was conducted to identify significant factors (<.05) to be included in a multivariate regression model. RESULTS: Assessments identified as independently associated with driving performance in the regression model included: FACTTM Contrast sensitivity slide-B, Rapid Pace Walk, UFOV rating, and MMSE total score. DISCUSSION: The domains of vision, cognitive, and motor performance were represented in the predictive model. SUMMARY: Due to the dynamic nature of the driving task, it is not likely that a single assessment tool will identify at risk drivers. IMPACT ON INDUSTRY: By standardizing the selection of clinical assessments used in driving evaluations, practitioners should be able to provide services more efficiently, more objectively, and more accurately to identify at-risk drivers.     

Socio-demographic and experience factors affecting drivers’ runoff risk along horizontal curves of two-lane rural highway

Introduction: An improper driving strategy is one of the causative factors for a high probability of runoff and overturning crashes along the horizontal curves of two-lane highways. The socio-demographic and driving experience factors of a driver do influence driving strategy. Hence, this paper explored the effect of these factors on the driver’s runoff risk along the horizontal curves. Method: The driving performance data of 48 drivers along 52 horizontal curves was recorded in a fixed-base driving simulator. The driving performance index was estimated from the weighted lateral acceleration profile of each driver along a horizontal curve. It was clustered and compared with the actual runoff events observed during the experiment. It yielded high, moderate, and low-risk clusters. Using cross-tabulation, each risk cluster was compared with the socio-demographic and experience factors. Further, generalized mixed logistic regression models were developed to predict the high-risk and high to moderate risk events. Results: The age and experience of drivers are the influencing factors for runoff crash. The high-risk event percentage for mid-age drivers decreases with an increase in driving experience. For younger drivers, it increases initially but decreases afterwards. The generalized mixed logistic regression models identified young drivers with mid and high experience and mid-age drivers with low-experience as the high-risk groups. Conclusions: The proposed index parameter is effective in identifying the risk associated with horizontal curves. Driver training program focusing on the horizontal curve negotiation skills and graduated driver licensing could help the high-risk groups. Practical applications: The proposed index parameter can evaluate driving behavior at the horizontal curves. Driving behavior of high-risk groups could be considered in highway geometric design. Motor-vehicle agencies, advanced driver assistance systems manufacturers, and insurance agencies can use proposed index parameter to identify the high-risk drivers for their perusal.     

铁路提速区段中间站行车安全评价的研究

分析了影响铁路提速区段中间站行车安全的主要因素;基于系统工程的理论原则,从人员安全保障、设备安全保障、环境安全保障、基础安全管理保障4个方面着手,确立了铁路提速区段中间站行车安全评价指标体系;运用模糊层次分析法,建立了评价模型;提出了铁路提速区段中间站行车安全保障模糊层次评价的一般方法;对我国铁路主干线某一提速区段中间站进行实例分析,其结果显示,基础安全管理占有十分重要的位置;最后,笔者建议,在我国铁路实现“客运高速、货运重载”的发展方向下,应当加强提速区段中间站的安全管理,认真进行行车安全评价,实现行车事故的预测与预防     

中美煤矿安全比较与借鉴

中国和美国都是煤炭生产和消费大国,但是中国的煤矿安全却与美国存在巨大差距。笔者首先从两国历年来煤矿安全数据分析入手,认为:美国煤矿安全经历了严重恶化、小幅波动和安全稳定3个阶段;而中国的煤矿经历了改革开放前大起大落和其后的小幅波动两个阶段,迄今为止,还没有进入安全稳定时期。然后从法规、监察、采矿权、安全投入、矿工及工会、教育及培训、科技进步等7个方面对两国的煤矿安全进行了比较。最后,借鉴美国进入第3阶段的成功经验,提出一些改善中国煤矿安全的相应对策建议,如完善法规、加强监管、明晰采矿权、设立安全投入预算资金、改善矿工的弱势地位、加强教育与培训、依靠科技进步等。     

Factors contributing to commercial vehicle rear-end conflicts in China: A study using on-board event data recorders

Introduction: In the last 30 years, China has undergone a dramatic increase in vehicle ownership and a resulting escalation in the number of road crashes. Although crash figures are decreasing today, they remain high; it is therefore important to investigate crash causation mechanisms to further improve road safety in China. Method: To shed more light on the topic, naturalistic driving data was collected in Shanghai as part of the evaluation of a behavior-based safety service. The data collection included instrumenting 47 vehicles belonging to a commercial fleet with data acquisition systems. From the overall sample, 91 rear-end crash or near-crash (CNC) events, triggered by 24 drivers, were used in the analysis. The CNC were annotated by three researchers, through an expert assessment methodology based on videos and kinematic variables. Results: The results show that the main factor behind the rear-end CNC was the adoption of very small safety margins. In contrast to results from previous studies in the US, the following vehicles' drivers typically had their eyes on the road and reacted quickly in response to the evolving conflict in most events. When delayed reactions occurred, they were mainly due to driving-related visual scanning mismatches (e.g., mirror checks) rather than visual distraction. Finally, the study identified four main conflict scenarios that represent the typical development of rear-end conflicts in this data. Conclusions: The findings of this study have several practical applications, such as informing the specifications of in-vehicle safety measures and automated driving and providing input into the design of coaching/training procedures to improve the driving habits of drivers.