恐惧诉求对职业驾驶员安全驾驶态度和行为意向的影响

研究以EPPM模型作为理论框架,探讨恐惧诉求对危险驾驶行为(超速和不系安全带)态度和行为意向的作用。54名职业驾驶员在观看交通安全恐惧诉求录像后,完成安全驾驶行为问卷。回归分析表明恐惧诉求的交通事故录像能够改变驾驶员对超速及不系安全带驾驶的态度和行为意向,但作用不完全一致。恐惧情绪唤起通过恐惧情感所引发的威胁评估过程中介对不超速行为意向的影响。最后,对研究的局限和未来的研究进行讨论。     

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。     

高原公路低氧路段驾驶疲劳脑电信号检测分析

为了解驾驶员在高原低氧路段的疲劳程度,以寻求缓解驾驶疲劳提高行车安全的途径,利用生物反馈检测仪分别对初次与经常进入高原公路低氧路段的驾驶员进行实地行车试验。通过对比不同海拔高度受测驾驶员脑电(EEG)变化特征,选取脑电8~13频段与14~30频段的平均功率比值R作为评价驾驶员疲劳时脑电特性指标R,定量分析海拔、连续驾驶时间对R的影响,同时建立R与海拔、连续驾驶时间之间的关系模型。研究表明:海拔与连续驾驶时间是影响驾驶员疲劳的主要因素,R随着海拔的升高与连续驾驶时间的增长而逐渐变大。初次在高原低氧路段行车的驾驶员表现出的疲劳感强于经常在高原低氧路段行车的驾驶员。     

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。     

交通主观安全感和客观安全感的博弈

安全交通行为主要表现在道路客观条件和道路使用者的交通安全意识的博弈。综述和评价交通心理领域主要的风险理论,行为-态度理论和任务-能力交互理论,总结出影响主观安全感和客观安全感的潜在因素和交互作用产生的博弈心理,试图揭示交通事故发生的个体层面的原因。分析结果表明:驾驶员安全驾驶行为是受到客观安全感(包括对路况、线性和道路环境等的评估)和个体主观安全感(主要是个性特征),这2种安全感的博弈共同影响着安全驾驶行为。     

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。     

基于贝叶斯结构方程模型的疲劳驾驶行为意图研究

为了深入探究影响驾驶员疲劳驾驶行为意图的心理因素,提高道路安全性,在计划行为理论的基础上,新增行为经验解释变量,形成扩展计划行为理论(Ex-TPB),构建了基于Ex-TPB的疲劳驾驶行为意图心理影响因素贝叶斯结构方程模型(Bayesian-SEM),并对比了传统结构方程模型(Traditional-SEM)与Bayesian-SEM的参数估计结果。最后,为有效防范疲劳驾驶行为提出了建议。结果表明:Ex-TPB可以有效解释和预测疲劳驾驶行为意图;在小样本的条件下Bayesian-SEM与Traditional-SEM相比,能得到更好的结果;对疲劳驾驶行为意图影响最大的因素为知觉行为控制,最小的是行为经验,且4种因素都显著正向影响疲劳驾驶行为意图。     

铁路道口安全影响因素分析及对策

在对比分析中外铁路道口安全形势及研究现状的基础上,从人、车、道口几何特性、安全防护装置、管理及环境等因素出发,系统地分析了铁路道口安全及其影响因素:1)汽车驾驶员酒后驾驶、超速驾驶、疲劳驾驶等人为违章行为是道口事故的主要致因;2)车辆机械故障、超载是影响道口安全不容忽视的重要因素;3)道口坡度、铺面、视距等道口几何特性与道口事故频率有着紧密联系;4)道口交通信号、车速监控器及惩罚对提高驾驶员的安全行为有显著作用;5)完善的应急医疗体系将大大减少道口事故的伤亡.进而从工程、教育和法制3方面提出了我国改善道口安全状况的措施和建议,包括:安装悬臂梁警告装置,施划减速标线,改造道口铺面,加大酒后驾驶惩罚力度,宣传道口安全知识等.     

地铁驾驶员驾驶疲劳状态监测

为监测地铁自动驾驶系统驾驶模式下驾驶员驾驶疲劳状态,以S地铁公司的驾驶员为研究对象,开展驾驶员疲劳主、客观监测研究。主观监测应用《自觉症状调查表》调查并统计分析地铁驾驶员的驾驶主观疲劳感受;客观监测应用Eegosports 64通道无线脑电肌电系统测量地铁驾驶员在各班次、各时间段的脑电(EEG)信号,并结合Matlab工具箱中的EEGLAB分析各班次驾驶员EEG中δ波的频谱图。结果表明:驾驶员驾驶疲劳总体的平均得分为1.8分,即驾驶疲劳有些明显,且晚班和夜班驾驶疲劳比白班的大,从主客观2方面说明驾驶员处于疲劳驾驶状态。     

Fatal crash trends for Australian young drivers 1997-2007: Geographic and socioeconomic differentials

Background

Little has been published on changes in young driver fatality rates over time. This paper examines differences in Australian young driver fatality rates over the last decade, examining important risk factors including place of residence and socioeconomic status (SES).

Methods

Young driver (17-25 years) police-recorded passenger vehicle crashes were extracted from New South Wales State records from 1997-2007. Rurality of residence and SES were classified into three levels based on drivers’ residential postcode: urban, regional, or rural; and high, moderate, or low SES areas. Geographic and SES disparities in trends of fatality rates were examined by the generalized linear model. Chi-square trend test was used to examine the distributions of posted speed limits, drinking driving, fatigue, seatbelt use, vehicle age, night-time driving, and the time from crash to death across rurality and socioeconomic status.

Results

Young driver fatality rate significantly decreased 5% per year (p < 0.05); however, stratified analyses (by rurality and by SES) showed that only the reduction among urban drivers was significant (average 5% decrease per year, p < 0.01). The higher relative risk of fatality for rural versus urban drivers, and for drivers of low versus high SES remained unchanged over the last decade. High posted speed limits, fatigue, drink driving and seatbelt non-use were significantly associated with rural fatalities, whereas high posted speed limit, fatigue, and driving an older vehicle were significantly related to low SES fatality.

Conclusion

The constant geographic and SES disparities in young driver fatality rates highlight safety inequities for those living in rural areas and those of low SES. Better targeted interventions are needed, including attention to behavioral risk factors and vehicle age.     

The use of technology to address patterns of risk among teenage drivers

INTRODUCTION: The crash risk of teens is high, with fatal crash rates of teen drivers higher than any other age group. New approaches to reduce teen traffic fatalities are clearly needed. METHOD: A possible approach to reduce the incidence of teen driver crashes and fatalities is through the use of vehicle-based intelligent driver support systems. To be most effective, the system should address the behaviors associated with an overwhelming number of teen fatal crashes: speed, low seatbelt use, and alcohol impairment. In-vehicle technology also offers an opportunity to address the issue of inexperience through enforcement of certain Graduated Driver's License provisions. RESULTS: To fully understand the capability of such technologies, there should be a concerted effort to further their development, and human factors testing should take place to understand their effects on the driver. IMPACT: If successfully implemented, a Teen Driver Support System (TDSS), such as the one described here, could significantly decrease the number of teens killed in traffic crashes.     

Multilevel modeling in traffic safety research: two empirical examples illustrating the consequences of ignoring hierarchies

OBJECTIVES: This commentary illustrates the advantages of multilevel modeling compared to statistical techniques that ignore hierarchies, based on two empirical traffic safety examples. METHODS: The common concept shared by different definitions of multilevel modeling is identified and illustrated. Each definition defines multilevel modeling in its own way but they all refer to hierarchies. Conceptual issues inherently related to hierarchies are then pointed out and illustrated. RESULTS: Broadly speaking there are two important consequences of ignoring a hierarchical structure in the data. The first consequence, underestimation of standard errors, is illustrated with data from an observational study on seatbelt behavior. Two effects that were significant at the 5% level in a single-level model were no longer found to be significant in a two-level model. The single-level model is therefore bound to lead to erroneous conclusions regarding variables that could have an impact on seatbelt use and, ultimately, on increasing the level of traffic safety. The second consequence, related to contextual information, is illustrated with data from a roadside survey on drink driving. Of particular interest is the relationship between Traffic Count, an aggregated level 2 explanatory variable and Odds of drink driving, an individual level 1 dependent variable. CONCLUSIONS: Like every statistical technique, multilevel models should be used with caution and reservation. However, given certain limitations, multilevel modeling is very useful and valuable to traffic safety research.     

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1370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...     

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.     

The prevalence of seatbelt and mobile phone use among drivers in Riyadh,Saudi Arabia: An observational study

IntroductionRoad traffic injuries (RTIs) are the third leading cause of death in Saudi Arabia. Numerous factors may increase the likelihood of RTIs. The prevalence of risk factors associated with RTIs may vary due to several reasons. Because little is known about these risk factors locally, we examined the prevalence of mobile phone and seatbelt use and their association with spatial locations.MethodsThis is an observational study conducted at major highways and inner intersections throughout Riyadh, the country's capital. Two observers captured seatbelt and mobile phone use among drivers. Logistic regression models were constructed to examine the association between real estate prices and mobile phone or seatbelt use. Observations were categorized as taken place in an affluent neighborhood if the average price per square meter was above 2500 Saudi Riyal.ResultsA total of 1700 drivers were observed in 13 sites citywide. 13.8% of drivers were seen using mobile while driving and only a third of drivers (34%) were wearing seatbelts. Being at an affluent neighborhood was associated with close to three times higher odds of wearing seatbelts (OR = 2.7, 95% CI = 1.9–3.7) and also associated with 42% lower odds of mobile phone use among drivers (OR = 0.58, 95% CI = 0.36–0.92).DiscussionThis study found a high prevalence of traffic violations among drivers in Riyadh. Based on our estimate, 660,000 drivers are roaming the street during daytime while using their phones and they are less likely to wear seatbelts. Unfortunately, this estimate might contribute to increasing RTIs. Despite existing regulations, seatbelt use among drivers is significantly lower than in developed countries (i.e. USA 94%).ConclusionOur study found a high prevalence of traffic violations represented by lack of compliance with seatbelt and mobile phone use laws. These findings provide a basis for their underlying prevalence in SA. Practical applications: Public health prevention programs may use these findings to facilitate support to increasing investment in awareness campaigns and further enforcement by the traffic police to reduce RITs and improve population health.     

Why is the rate of annual road fatalities increasing? A unit record analysis of New Zealand data (2010–2017)

IntroductionRecent increases in road crashes have reversed New Zealand’s formerly declining crash rates to produce annual fatal and serious injury counts that are 49% higher than the lowest rates achieved in 2013. Method: We model twenty-one factors in fatal and serious injury crashes, four years before and after 2013 using logistic regression. Three major factors are significantly different in the period after 2013, when crash rates increased: (1) alcohol as a cause, (2) learner licence holders, and (3) a regional effect for Auckland. Newly defined speed zones are a more common setting for crashes in the period of upturn but there is no coinciding elevated likelihood of ‘speed as a causal factor’. Three factors related to road safety were less common: aged under 25-years old, fatigue, and not wearing a seatbelt. Results: Results are compared to rates of prosecutions for alcohol-related driving offences over this period. It is possible that New Zealand’s successful road safety initiatives of the past have been undermined by reduced levels of enforcement and an unexpected outcome from the graduated driving licence system.     

基于计划行为理论的自行车不安全行为模型研究

依托国家道路交通安全科技行动计划课题五"全民交通行为安全性提升综合技术及示范"专题,基于计划行为理论,从社会心理学的角度首次对自行车骑行者的不安全行为进行分析。在增加变量的基础上,通过调查问卷的方式,研究自行车骑行者对不安全行为的态度、主观规范、知觉行为控制、行为经验等心理因素,从而构建自行车不安全行为模型。从调查数据的结构方程模型分析和个人属性分析可知,在调查人群中存在对不安全行为没有正确认识、自觉守法能力较弱和普遍有不安全行为经验等问题,同时也确定了参与不安全行为的重点人群。最后,在揭示心理因素作用于行为的基础上提出家庭式安全教育、加强交警管理、提倡榜样学习、加强交通安全宣传等行为矫正手段。     

The effect of fatigue driving on injury severity considering the endogeneity

IntroductionFatigue driving is one of the most risky driving-related behaviors and represented a significant social and economic cost to the community. Several studies have already examined the relationship between fatigue driving behavior and traffic injury severity from different aspects. However, fatigue driving and injury severity in traffic crash may share some common influential factors. Ignoring the impact of these common factors will lead to endogeneity problem and result in biased parameter estimation.MethodBased on 38,564 crash records during 2006–2011 in Guangdong province, China, we apply a bivariate endogenous binary-ordered probit model to examine the relationship between fatigue driving and injury severity considering endogeneity of fatigue driving. We also explore the difference of influential factors between commercial and non-commercial vehicle drivers.ResultsThis study identifies several common observed influential factors of fatigue driving propensity and fatal injury propensity and reveals a substantial and significant negative correlation of unobserved factors between them.ConclusionsThe influence of fatigue driving on injury severity is significantly underestimated if the endogeneity of fatigue driving on fatal injury propensity is ignored. Factors such as vehicle insurance and road types not only affect fatal injury propensity, but also fatigue driving propensity.Practical applicationsThe findings in this study can help better understand how those factors affect fatigue driving and injury severity, and contributes to more efficient policy for preventing the harmfulness of fatigue-related crashes.