Relationship between traffic fatalities and drunk driving in Japan

OBJECTIVE: The present study was performed to clarify the relation between alcohol use and traffic fatalities in accidents involving motor vehicles in Japan. METHODS: Data on traffic accidents were collected from Fukuoka Prefectural Police records of traffic accidents which occurred in that prefecture between 1987 and 1996. Multiple logistic regression models were used to assess the effect of alcohol use on the risk of traffic-accident death. RESULTS: The data showed that 58,421 male drivers were involved in traffic accidents during the 10-year study period, and that 271 of these were killed as a result of the accident. Alcohol use was significantly associated with speed, seat belt use, time, and road form. Among male motorcar drivers, the odds ratio of alcohol use before driving, after adjusting for age, calendar year, time, and road form, was 4.08 (95% confidence interval, 3.08-5.40), which means that about 75% of fatalities (attributable risk percent among exposed) might have been prevented if drivers had not drunk before driving. CONCLUSIONS: Alcohol use before driving resulted in a 4.08-fold increase in the risk of death in a traffic accident. It is suggested that alcohol use is considered an important risk factor for fatality in traffic accidents.     

危险化学品运输管理及事故应急系统探讨

通过全球定位系统(GPS)、地理信息系统(GIS)、专家系统(ES)、自动监测等技术的集成,充分发挥各自技术的优势,建立危险化学品运输及事故应急系统。该系统由基于GPS技术的“运输车辆管理”、基于自动监测技术的“事故自动报警”、基于扩散数学模型和GIS技术的“泄漏模拟分析”、基于专家系统的“事故应急救援”以及基于Web技术“信息发布及数据维护”等5个子系统组成,通过集成各子系统实现危险化学品运输管理的自动化、智能化,在事故发生的第一时间自动报警,避免因人为因素而贻误救援时间,同时通过现场信息数据分析做出最有效的救援安排。     

Applying linear analysis methods to GIS-supported procedures for preventing traffic accidents: Case study of Konya

This study develops methods to obtain maps to determine traffic Hot Spots in Konya, Turkey, by applying linear analysis supported by Geographical Information Systems (GIS).Hot Spot analysis is known method but the study differs from former researches at the point of determining of risky zones, classification and illustration of them on the maps with the different accident parameters. The aim is not to contribute another Hot Spot analysis using a number of statistical methods, but to determine the Highest Potential Hot Spots (HPHS), which are inter-sectional clusters, and to use different parameters, such as number of accidents, number of fatalities and injured, and number of accidents with only financial loss.In addition, apart from classical illustrational techniques, Hot Pieces (HPCS) on roads divided into 1 km segments are shown by their grading according to their numerical values. Hence, thematic illustration distinguishes them from others.Another aspect of this study is that, besides investigation of Hot Spots by means of data of accidents of previous years’, Probable Hot Spots (PRHS) were illustrated and highly potential Hot Spots were determined. These latter are candidates for Hot Spots in the near future. Thus, premature accidents can be anticipated easily.The main intention of this study is to emphasize the importance of using criteria, other than total accident number, to illustrate intersection Hot Spots and to constitute a model of accident severity and variety. It is anticipated that the results obtained from highway accidents data will guide improvement of the route segments.     

Personal exposure risk factors in pedestrian accidents in Bahrain

Pedestrians are involved in traffic accidents due to many reasons. It is generally thought that personal background of pedestrians has an effect on their involvement rate in the road traffic accidents. Identifying these characteristics would lead to a better understanding of pedestrian accident pattern so that the resources in the field of education, engineering, and enforcement could be used in better ways. This study attempts to test the hypothesis mentioned earlier. The investigated personal background includes the following characteristics: gender, type, age, nationality, and educational background. The data was reduced from vast number of pedestrian injury accident reports in the Kingdom of Bahrain. The actual accident records were categorized according to these characteristics and compared to their exposure risk. It was assumed that the exposure risk, which is the expected number of accidents for each category of the pedestrians, was in proportion to their presence in the pedestrian population. Another study was carried out in parallel to observe the pedestrian characteristics in Bahrain. The results of the two studies were analyzed statistically using Chi-square method to compare the actual to the expected accident frequencies. The whole Kingdom of Bahrain population statistics were used wherever the information on the pedestrian population was not available. The findings revealed that personal characteristics considered in this study have significant influence on pedestrian’s involvement in traffic accidents. The results also showed that pedestrians with the following characteristics were probably showing risk to exposure to accidents more than other categories: male, young (0–12 years) and old (50 years and over), non-local, and those with low educational background.     

交通事故信息管理与时空分布分析

交通事故发生点具有明确的空间位置属性 ,其在空间和时间上的分布具有不均匀性 ,利用GIS技术能实现交通事故信息管理及其时空分布规律的研究。笔者在分析道路交通事故信息的基础上 ,采用全新的管理模式 ,利用空间数据库技术实现交通事故的空间、时间信息以及造成交通事故的人、车、路和环境等因素的一体化管理 ;通过GIS技术进行道路交通事故的时空分布分析 ,发现其在空间和时间上的分布规律 ;最后提出了交通事故管理与分析中需要进一步解决的几个问题。     

城市道路交通事故地点文字表述方法研究

法律文书和交通安全分析要求事故地点记录准确、规范。为规范事故地点记录,在总结国外事故地点记录的点-线法、无规范格式法、线性参照系法、经纬度坐标法基础上,结合国内城市事故定位工作的需求,提出基于线性参照系的"五要素"事故地点文字表述方法。针对城市复杂道路网络,在道路分类的基础上,结合现场记录要求定义和说明"五要素"(事故所在道路、路侧、参照点、方位、距离),最后提出基于"五要素"的文字组合表述方法和事故地点记录实施方案。事故地点"五要素"记录法可供各地在改进事故地点记录时借鉴以提高事故数据的规范性。     

Road traffic accident severity analysis: A census-based study in China

Background: In China, despite the decrease in average road traffic fatalities per capita, the fatality rate and injury rate have been increasing until 2015. Purpose: This study aims to analyze the road traffic accident severity in China from a macro viewpoint and various aspects and illuminate several key causal factors. From these analyses, we propose possible countermeasures to reduce accident severity. Method: The severity of traffic accidents is measured by human damage (HD) and case fatality rate (CFR). Different categorizations of national road traffic census data are analyzed to evaluate the severity of different types of accidents and further to demonstrate the key factors that contribute to the increase in accident severity. Regional data from selected major municipalities and provinces are also compared with national traffic census data to verify data consistency. Results: From 2000 to 2016, the overall CFR and HD of road accidents in China have increased by 19.0% and 63.7%, respectively. In 2016, CFR of freight vehicles is 33.5% higher than average; late-night accidents are more fatal than those that occur at other periods. The speeding issue is severely becoming worse. In 2000, its CFR is only 5.3% higher than average, while in 2016, the number is 42.0%. Conclusion and practical implementation: A growing trend of accident severity was found to be contrasting to the decline of road traffic accidents. From the analysis of casual factors, it was confirmed that the release way of the impact energy and the protection worn by the victims are key variables contributing to the severity of road traffic accidents.     

Behavior and lifestyle characteristics of male Kuwaiti drivers

Introduction: The high traffic accident risk among young drivers is a well-known and well-documented fact in most countries. Lifestyle has proven to affect driving behavior as well as accident risk. This study covers the lifestyle component of the problems related to young male Kuwaiti drivers’ accident risk. Methods: The purpose of the study is to measure the relationship between lifestyle and accident risk. Lifestyle is measured through a questionnaire, where 302 male Kuwaiti drivers (mean age = 28 years; range 25-35 years) answer 39 questions related to behavioral and social factors, road conditions, police enforcement, and life satisfaction. They also report their involvement in accidents and traffic violations. Results: The questionnaire's validity and reliability (Cronbach's alpha = 0.7) were achieved. Principal component analysis reduced the 39 items on the questionnaire to 5 factors. Inadequate police enforcement is strongly correlated (r = 0.862) to accident risk and traffic violations and is thus considered the best predictor of traffic accidents in Kuwait. Impact on Industry: As driving-related incidents (on-the-job and off-the-job) are a significant source of fatalities and lost-work-days, the study points to the importance of considering cultural factors in the design of comprehensive safety programs for industry.     

基于贝叶斯网的交通事故机理分析

针对道路交通事故的形成机理进行定性、定量研究,根据我国道路交通事故记录数据特征,应用贝叶斯网对事故发生概率进行定量分析.引入"驾驶员紧张度"和"道路线形合理度"两个隐节点,建立了事故分析的贝叶斯网多层隐类模型,采用最大似然估计方法确定了模型的边缘概率和条件概率.将贝叶斯网模型应用于国道104二级公路(K1310+000～K1330+000)的事故分析中,运用贝叶斯网分析软件包Netica对其历史事故记录数据进行分析.结果表明: 贝叶斯网不仅可以定量计算某种道路交通状态下的事故发生概率,而且可以找出影响事故概率的关键原因和最不利状态组合(事故概率最大时的道路交通状态).     

Risky driving and the perception of motorcycle accident causes among chinese motorcyclists in Hong Kong

Objective: The primary purposes of this study were to explore the relationship between risk-taking acts while driving motorcycles and perceived causes of motorcycle accidents, as well as their contribution to active involvement in traffic accidents among Chinese motorcyclists in Hong Kong. Active involvement means the riders was likely at fault for the crash. Methods: A total of 774 motorcyclists were recruited, of whom 292 had been involved in active motorcycle accident in the previous 3?years. All were asked to fill in a questionnaire, which was developed to assess their risk-taking acts while driving a motorcycle and perception of motorcycle accident causes. Results: The results of the study revealed 3 dimensions of accident causes, namely, driving-related, environment-related, and belief-related causes. These motorcycle accident causes were correlated with risk-taking acts while driving a motorcycle. A multivariate logistic regression analysis showed that risk-taking acts while driving motorcycles (adjusted odds ratio [OR]: 1.036, 95% confidence interval [CI]: 1.020-1.052), perception of driving-related cause (adjusted OR: 0.941, 95% CI: 0.916-0.967), and belief-related cause (adjusted OR: 1.134, 95% CI: 1.088-1.182) were significant factors contributing to involvement in active traffic accidents by motorcycle riders after controlling for concurrent demographic variables. Conclusions: The study highlights that perceived causes of motorcycle accidents are multidimensional, including those areas related to driving, the environment, and beliefs. It substantiates previous studies that a higher degree of driving-related risk perception is related to a lower degree of risk-taking acts while driving. Further research is needed to understand why belief-related causes, sometimes called superstitions, lead riders to believe that it is beyond their ability to affect accident causation and prevention.     

基于APRIORI-TAN的交通事故伤害分析与预测*

为探究道路交通事故因素和事故伤害的相关性,以2 467起涉及人员伤亡的交通事故为数据集,运用Apriori算法分别挖掘事故伤害关联规则,并结合社会网络分析的可视化和核心-边缘分析构建受伤事故和死亡事故的关联规则网络。结果表明:事故伤害程度与事故时间、道路条件和交通环境等因素关系紧密,尤其死亡事故与碰撞固定物、人行横道事故、高速公路、高速道路、非市区、酒驾和超速存在高相关性。基于树型贝叶斯网络（TAN）构建事故伤害程度的预测模型,预测结果准确率可达87.56%。     

从道路交通事故统计分析对比谈预防措施

笔者通过对比我国与世界上部分发达国家近十年来在道路交通事故方面的统计数据 ,并根据经济发展水平与机动车保有量的正比例关系及当前我国道路交通事故现状 ,分析得出道路交通安全事故的发生 ,与人、车辆、道路、环境信息及管理等因素具有密切关系 ,其中人 (尤其是驾驶员 )作为交通行为的主体 ,是道路交通事故诱因中一个关键性因素。由此 ,作者提出了要有效预防和减少道路交通事故的发生 ,必须将人、车、路、环境信息和管理等诸因素作为一个有机整体系统思考 ,且在未来的道路交通发展中应引入交通稳静化理念 ,以实现道路交通的安全、畅通与高效     

基于最优尺度Logit模型的交通事故形态致因分析

为剖析典型交通事故形态致因,在利用最优尺度分析法诊断交通事故形态致因共线性的基础上,筛选关键影响因素,构建无序多分类Logit交通事故致因模型并对模型进行参数标定,并选择100个交通事故样本对模型进行精度验证,该模型相对误差仅为4.0％,能够较为准确地分析典型交通事故形态致因.研究结果表明:路侧及中央隔离设施、照明是事...     

北京市道路交通安全现状分析及控制策略研究

在分析北京市道路交通安全形势以及事故特点的基础上,运用交通冲突理论分析道路交通事故发生的机理,论述道路交通事故发生的过程。并从安全系统工程学角度,使用交通事故显性/隐性致因模型对道路交通事故的致因因素进行分析,强调管理因素的重要性。最后,结合北京市道路交通现状,综合运用3E对策,讨论了改善道路交通安全的控制策略。通过加大违章行为惩罚力度、培养安全文化、建立道路交通事故应急救援体系以及应用智能交通技术等措施,消除道路交通系统中人的不安全行为和物的不安全状态,提高北京市道路交通安全水平。     

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials

IntroductionThe effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece.MethodRandom Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively.ResultsRegarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity.ConclusionsThe study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms.Practical applicationThe identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials.     

基于模糊Petri网的交通事故致因建模分析

针对目前我国道路交通事故多发的现状,以模糊Petri网为工具,以对道路交通安全有重大影响的关键因素为基础,模拟给出其因果关系,建立了基于模糊Petri网的道路交通事故致因分析模型,设计最长路径算法分析模型中某个致因要素导致交通事故发生的可信度。最长路径上的致因要素即为最易引起交通事故的主要因素。案例分析表明,这个模型能够体现各因素之间的逻辑关系,达到了通过数量指标分析道路交通事故主要原因的目的。     

超大城市昼夜交通事故严重程度致因对比分析——以深圳市为例

为研究夜间交通事故严重程度致因，基于深圳市3年3 244起交通事故数据，获取昼夜交通事故分布的时空特征；进一步选取交通事故集聚的南山区、福田区、罗湖区的1 798起交通事故，以交通事故严重程度为因变量，以事故原因、日期、事故形态等10个因素为候选自变量，构建广义有序Logit回归模型，对比分析昼夜不同严重程度交通事故的影响因素。结果表明:路口路段类型、疲劳驾驶、事故日期在夜间模型参数估计值分别为0.493，-0.363，-0.309，而在日间模型表现为不显著，道路路面材料在日间模型参数估计值为-0.232，而在夜间表现为不显著；事故原因、道路横断面渠化方式等因素在日间和夜间所引起交通事故的严重等级均存在较大差异。     

Data fusion,ensemble and clustering to improve the classification accuracy for the severity of road traffic accidents in Korea

Increasing amount of road traffic in 1990s has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving environmental factors based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we use various algorithms to improve the accuracy of individual classifiers for two categories of severity of road traffic accident. Individual classifiers used are neural network and decision tree. Mainly three different approaches are applied: classifier fusion based on the Dempster–Shafer algorithm, the Bayesian procedure and logistic model; data ensemble fusion based on arcing and bagging; and clustering based on the k-means algorithm. Our empirical study results indicate that a clustering based classification algorithm works best for road traffic accident classification in Korea.     

Driver personality characteristics related to self-reported accident involvement and mobile phone use while driving

A causal model was developed in this study to clarify the effect of mobile phone use on driving safety. Based on the model, a series of questionnaires were developed, and 194 car drivers were interviewed based on these questionnaires. Results showed that perceived risk and mobile phone usage habits varied with different individual traits. Drivers who were prone to accidents revealed a lower perception of safety risks and a higher self-reported accident rate resulting from mobile phone use than those who were not accident-prone. Aggressive drivers were found to use mobile phones more frequently while driving but had a similar accident rate to non-aggressive drivers. Frequency in mobile phone use while driving significantly increased among aggressive male drivers regardless of accident proneness. Findings from this study imply that the perceived risk of drivers might be an ignored but important factor in the relationship between mobile phone use and driving safety. Because of the difficulty in practically identifying who is accident-prone or not, this study suggests that overall prohibition in mobile phone use while driving is needed to reduce the corresponding number of traffic accidents.     

道路交通事故发展趋势分析与预测

根据福建省2000 -2010年交通事故相关指标,采用统计图表分析法进行交通事故发展趋势分析与安全水平比较研究,结果表明交通事故各项绝对指标总体呈下降趋势,但从万车死亡率、受伤人数与死亡人数比及交通事故死亡人数占各类事故死亡人数比重等相对指标看,交通安全总体水平偏低,交通事故后果比较严重.对交通事故死亡人数与GDP、机动车保有量、公路通车里程、人口数四项影响因素进行了多元线性回归分析,分析得出四个影响因素总体对交通事故死亡人数的线性影响是显著的,采取向后筛选策略线性回归分析得出,死亡人数与GDP的线性关系是显著的,根据回归结果建立了交通事故的预测模型.