Long-term prediction of traffic accident record from bus driver celeration behavior.

Driver celeration (speed change) behavior of bus drivers measured a number of times was used to predict their culpable accidents over increasing time periods. It was found that predictive power was considerable (>.30 correlation) over 5 years of time with aggregated celeration (mean of repeated measurements) as independent variables, and there were also indications that power reached even further, although too low Ns made these results unreliable. Similarly, there were indications of even stronger correlations with increased aggregation of celeration values. The results were discussed in terms of the methodology needed to bring out such results, and the stability of accident-causing behavior over time.     

Speed choice versus celeration behavior as traffic accident predictor

INTRODUCTION: The driver celeration behavior theory predicts that this variable is superior to all other variables as a predictor of individual traffic accident involvement, including the ever-important speed parameter. The study was undertaken to test this prediction. Also, it was expected that most variables would associate fairly strongly. METHOD: The use of speed choice as a predictor of individual traffic accident record was discussed, and four different variants of this variable (maximum, net mean, gross mean, and standard deviation of speed) identified. These variables were then compared to celeration behavior as predictors of accident record of bus drivers in the same set of data. RESULTS: Celeration behavior was found to be slightly superior, in accordance with the prediction made from the driver celeration behavior theory, although the differences were not significant. Furthermore, the predictor variables were found to associate fairly strongly between themselves, with the exception of gross mean speed, and to have fair stability over time, especially when aggregated. CONCLUSIONS: These results tentatively confirm some of the predictions made from the driver celeration behavior theory. As the results for accidents were in the expected direction, but not significant, and the maximum speed variable may have suffered from a ceiling effect, the conclusion is provisional. Impact on industry: The correlations found were strong enough to warrant the use of celeration behavior as a predictive variable for transportation companies in their safety work.     

The relation of non-culpable traffic incidents to bus drivers' celeration behavior

PROBLEM: The driver celeration behavior theory predicts that celerations are associated with incidents for which the driver has some responsibility in causing, but not other incidents. METHOD: The hypothesis was tested in 25 samples of repeated measurements of bus drivers' celeration behavior against their incidents for two years. RESULTS: The results confirmed the prediction; in 18 samples, the correlation for culpable incidents only was higher than for all incidents, despite the higher means of the latter. Non-culpable incidents had correlations close to zero with celeration. DISCUSSION: It was pointed out that most individual crash prediction studies have not made this differentiation, and thus probably yielded underestimates of the associations sought, although the effect is not strong, due to non-culpable accident involvements being few (less than a third of the total). The methods for correct identification of culpable incident involvements were discussed.     

Effects of passengers on bus driver celeration behavior and incident prediction

PROBLEM: Driver celeration (speed change) behavior of bus drivers has previously been found to predict their traffic incident involvement, but it has also been ascertained that the level of celeration is influenced by the number of passengers carried as well as other traffic density variables. This means that the individual level of celeration is not as well estimated as could be the case. Another hypothesized influence of the number of passengers is that of differential quality of measurements, where high passenger density circumstances are supposed to yield better estimates of the individual driver component of celeration behavior. METHOD: Comparisons were made between different variants of the celeration as predictor of traffic incidents of bus drivers. The number of bus passengers was held constant, and cases identified by their number of passengers per kilometer during measurement were excluded (in 12 samples of repeated measurements). RESULTS: After holding passengers constant, the correlations between celeration behavior and incident record increased very slightly. Also, the selective prediction of incident record of those drivers who had had many passengers when measured increased the correlations even more. CONCLUSIONS: The influence of traffic density variables like the number of passengers have little direct influence on the predictive power of celeration behavior, despite the impact upon absolute celeration level. Selective prediction on the other hand increased correlations substantially. This unusual effect was probably due to how the individual propensity for high or low celeration driving was affected by the number of stops made and general traffic density; differences between drivers in this respect were probably enhanced by the denser traffic, thus creating a better estimate of the theoretical celeration behavior parameter C. The new concept of selective prediction was discussed in terms of making estimates of the systematic differences in quality of the individual driver data.     

高速公路交通事故的季节变动规律分析及预测

根据京沪高速某段近五年的交通事故数据,首先通过测算该段交通事故的季度季节性指标,得出该段交通事故的季节变动程度明显;其次通过进一步测算交通事故的月份、星期、年均日、年均日24小时季节性指标和分析其趋势,得出该段交通事故高峰期出现在一季度,1月、2月、4月、10月,每月的月初和月末以及每天的凌晨1点左右、上午10点左右、下午4点左右;最后根据季节性指标构建了季节性预测模型.研究方法对其他高速公路季节变动规律分析具有参考作用,研究结论对不同时间内如何采取不同的安全对策来降低高速公路交通事故具有指导作用.     

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.     

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。     

摩托车头盔与摩托车交通事故的相关研究

我国近年来的摩托车死亡事故占交通事故死亡总数的25％-28％。在我国摩托车使用比较普及的地区,摩托车交通事故数占到该地区交通事故总数的70％-80％,伤亡比例占到总数的50％以上,甚至更高。通过对摩托车交通事故伤亡人员的具体受伤部位分析,发现头部受伤致死的比例非常高,占到该类事故死亡总数75％以上,远远高于其他部位受伤致死率。摩托车驾乘人员头部受伤致死的主要原因是摩托车驾驶乘人员头盔佩戴率低和佩戴的头盔质量差,对头部未能起到应有的保护作用。造成这一局面既有摩托车乘员头盔标准等技术层面存在的问题,又有行业监管等政策层面存在的问题,最后,文章从摩托车头盔标准方面提出了几点修订建议,为规范头盔行业进行基础性的准备。     

交通运输企业交通事故法律适用问题探讨

交通运输企业的交通运输事故法律适用问题引起了社会广泛争议。如不明确这个问题,对于执法主体、执法权限就不能明确,既会产生安全管理的盲区,有时候也会损害企业的相关权益。文章对《中华人民共和国安全生产法》适用范围条款进行了分析解读,阐明道路交通运输企业的交通运输安全问题既适用《安全生产法》,也适用《道路交通安全法》,二法之间不会有交叉,更不会产生冲突;同时也对道路交通事故的属性进行了分析,并探讨了交通运输企业交通事故的法律适用问题。     

我国交通事故分析与控制对策研究

在分析我国交通事故现状及原因的基础上,利用安全系统工程的原理,提出了控制交通事故的基本对策。     

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.     

城市交通事故现场处理时间及影响因素分析

为了分析城市交通事故现场处理的时间长度和影响因素,以城市交通事故现场处理时间为研究对象,将城市交通事故现场处理的过程细分为划定警戒区域、现场勘查、撤除现场3个阶段,运用事故现场数据采集和视频数据提取的方式,采集了 829条泸州市城市交通事故现场处理数据,从中提取可能影响城市交通事故现场处理时间的4个事故相关因素、5个现场处理相关因素和3个环境因素.以城市交通事故现场处理时间为因变量、12个可能的影响因素为自变量,采用逐步回归的方法提取显著影响因素.结果表明,城市交通事故现场处理的平均时间为15.28 min,警戒区域占道情况、当事人确认情况、事故发生时间和事故严重程度是影响城市交通事故现场处理时间的最主要因素,围观群众影响情况、事故类型、天气情况、道路等级和事故发生时段对城市交通事故现场处理时间也有一定的影响.模型验证表明,所建立的回归模型平均相对误差为3.95％,具有较好的适应性.     

Risk factors affecting the severity of traffic accidents at Shanghai river-crossing tunnel

Objective: With increasing traffic volume and urban development, increasing numbers of underground tunnels have been constructed to relieve conflict between strained land and heavy traffic. However, as more long tunnels are constructed, tunnel traffic safety is becoming increasingly serious. Thus, it is necessary to acquire their implications and impacts. This study examined 4,539 traffic accidents that have occurred in 14 Shanghai river-crossing tunnels for the period 2011–2012 and analyze the correlation between potential factors and accident injury severity.

Methods: An ordered logit model was developed to examine the correlation between potential factors and accident injury severity.

Results: Results show that increased injury severity is associated with male drivers, drivers aged 65 years or older, accident time from midnight to dawn, weekends, wet road surface, goods vehicles, 3 or more vehicles, 4 or more lanes, middle speed limits (50–79 km/h), zone 3, extra-long tunnels (over 3,000 m), and maximum longitudinal gradient.

Conclusions: This article aims to provide useful information for engineers to develop interventions and countermeasures to improve tunnel safety in China.     

Investigation on the role of traffic volume in accidents on urban highways

Introduction

Roadway safety is a major concern for the general public and public agencies, as roadway crashes claim many lives and cause substantial economic loss each year. In Iran, a large number of vehicles are involved in road accidents each year, which cause many deaths and extensive property damage; such accidents are among the major causes of death and disability in the country. Method: To reduce roadway accidents, the factors that affect the occurrence and severity of accidents should be scrutinized to prevent or reduce their effect. The method that many researchers have adopted to determine the effective parameters surrounding road accidents in recent years is through statistical modeling of accidents. In this article, the role of different kinds of vehicles in traffic flow are investigated separately in terms of the likelihood of crashes on urban highways, and the vehicles are divided into three groups: passenger cars, heavy vehicles, and light non-passenger car vehicles. Poisson and negative binomial (NB) regression models were applied to model the accidents in this research, which were categorized into two groups: no injury (property damage only) accidents and more severe (injury and fatal) accidents. Results: Ultimately, we conclude that light non-passenger car vehicles (i.e., taxis and motorcycles) play the largest role in the occurrence of crashes on urban highways for both types of accidents.     

The Driver Behaviour Questionnaire as a predictor of accidents: a meta-analysis

Introduction

Through a meta-analysis, this study investigated the relation of errors and violations from the Driver Behaviour Questionnaire (DBQ) to accident involvement.

Method

We identified 174 studies using the DBQ, and a correlation of self-reported accidents with errors could be established in 32 samples and with violations in 42 samples.

Results

The results showed that violations predicted accidents with an overall correlation of .13 when based on zero-order effects reported in tabular form, and with an overall correlation of .07 for effects reported in multivariate analysis, in tables reporting only significant effects, or in the text of a study. Errors predicted accidents with overall correlations of .10 and .06, respectively. The meta-analysis also showed that errors and violations correlated negatively with age and positively with exposure, and that males reported fewer errors and more violations than females. Supplementary analyses were conducted focusing on the moderating role of age, and on predicting accidents prospectively and retrospectively. Potential sources of bias are discussed, such as publication bias, measurement error, and consistency motif.

Impact on Industry

The DBQ is a prominent measurement scale to examine drivers’ self-reported aberrant behaviors. The present study provides information about the validity of the DBQ and therefore has strong relevance for researchers and road safety practitioners who seek to obtain insight into driving behaviors of a population of interest.     

公路交通事故危险性与事故原因的灰色关联分析

交通安全既可以采用交通事故次数来评价，也可以根据交通事故的严重度进行衡量。不同的交通事故诱因，其事故后果的危险程度也不一致。运用灰色系统理论，以某段道路上交通事故多发点的“地点危险指数”为参考数列，以这些地点的不同事故诱因为比较数列，对“事故危险指数”和引发交通事故的各类事故原因之间作灰色关联分析，可以找出该路段上危害性最大的一些交通事故成因，在交通管理和交通安全宣传教育中有针对性地进行防治。本文以107国道1716—1883公里的交通事故数据为例给出了算例。