Statistical data analyses to elucidate the causes and improve the countermeasures for preventing train accidents in Japan

We investigate train accident data in Japan to elucidate the causes and improve the countermeasures for reducing the number of train accidents. We deal with statistical data on train accidents in the last 15 years, including frequency, types such as derailment and crash, causes and consequences. We review the historical trend of train accidents by applying a statistical modeling approach dealing with both serious accident data and total number of accidents. Probability distributions for explaining this train accident data are shown. We show the results of quantitative data analyses on the train accidents, that occurred at the ground‐level crossing and the relationship among utility type of railway company, equipment at the crossing and consequences of the accidents. Probabilistic mathematical models are used in the analyses. Finally, we try to evaluate the effectiveness of the countermeasures for preventing train accidents.     

煤矿机电及运输事故防治的紧迫性研究

分析了2005—2010年全国煤矿死亡事故中顶板、瓦斯、水灾、火灾、运输、机电、爆破等各类事故数占事故总数的比例及每起事故的平均死亡人数,指出运输和机电事故死亡人数分别居第3位和第5位,共占死亡总人数的13.72%;指出电气火源是引爆瓦斯的第一火源,且2010年由机电事故引发的矿井火灾占火灾事故总数的80%,得出加强煤矿机电事故防治工作是遏制瓦斯爆炸事故及矿井火灾的迫切需要的结论;最后指出,应加强机电及运输事故防治工作,以减少由煤矿机电、运输事故引发的瓦斯爆炸事故和火灾事故。     

LPG储罐事故危险特性动态模拟评价方法及软件开发

对LPG危险特性、易发事故及其发生机理进行全面系统地分析、归纳和分类,按LPG储罐事故可能发生的先后顺序．将其事故类型分为六类,建立了一套可描述事故特征参数随时间和距离的变化过程的LPG储罐事故危险特性动态模拟评价系统方法。为便于推广和实际应用,根据水平喷射火的特殊形状,提出了其人员伤亡人数和直接财产损失计算方法;将改进的喷射流扩展半径表达式用于喷射火模拟评价,将修正的TNO爆炸特征曲线拟和关系式和蒸气云爆炸人员伤亡距离关系式等改进方法应用于蒸气云爆炸模拟评价。结合Visual C 编程语言与MATLAB仿真技术,实现了事故后果动态模拟的软件化、可视化。本方法对有效预测、预防、控制LPG危险源事故具有重要工程应用价值和指导意义。     

Accident history,risk perception and traffic safe behaviour

Abstract

This study clarifies the associations between accident history, perception of the riskiness of road travel and traffic safety behaviours by taking into account the number and severity of accidents experienced. A sample of 525 road users in Cameroon answered a questionnaire comprising items on perception of risk, safe behaviour and personal accident history. Participants who reported involvement in more than three accidents or involvement in a severe accident perceived road travel as less risky and also reported behaving less safely compared with those involved in fewer, or less severe accidents. The results have practical implications for the prevention of traffic accidents.

Practitioner Summary: The associations between accident history, perceived risk of road travel and safe behaviour were investigated using self-report questionnaire data. Participants involved in more than three accidents, or in severe accidents, perceived road travel as less risky and also reported more unsafe behaviour compared with those involved in fewer, or less severe accidents. Campaigns targeting people with a less serious, less extensive accident history should aim to increase awareness of hazards and the potential severity of their consequences, as well as emphasising how easy it is to take the recommended preventive actions. Campaigns targeting those involved in more frequent accidents, and survivors of serious accidents, should address feelings of invulnerability and helplessness.     

Musculoskeletal injuries among bus drivers due to motor vehicle accidents and hazardous environmental conditions

A survey was conducted to identify causative circumstances of accidents resulting in musculoskeletal injury to bus drivers either when involved in motor vehicle accidents (MVAs) or even when the bus is not in motion, non-motor vehicle accidents (non-MVAs). Within a major bus transport corporation (about 2900 drivers) 2520 accidents occurred within a period of 5 years. Of these, 398 cases were analysed in which clinical and radiological evidence of a musculoskeletal injury existed, and which led to at least 10 days of absence from work. The 398 accidents were classified as MVAs and non-MVAs and each category was subsequently subclassified according to the different circumstances of occurrence. Matching the types of injury with the circumstances of occurrence of the accidents allowed several conclusions to be drawn and suggestions to be made for eliminating the hazards of musculoskeletal injury to bus drivers.     

Hazard analysis in chemical complexes in Japan—especially those caused by human errors

Accidents al Japanese chemical industrial complexes are examined from the past to the present at the Chiba, Mizushima, Sakai-Senpoku, Yokkaichi, Kashima and Tokushima-Ohtake areas. Comparisons with the number of accidents caused by hard errors and soft errors were made; where the hard errors are defined as the faults of the machines and facilities and the soft errors as the human errors and the faults of the systems. The results may be summarized as follows: the ratio of the number of accidents caused by the hard errors to the soft errors was approximately 2:3 at all areas. Using the data obtained through a questionnaire on the potential accidents from about 200 workers engaged in the chemical industry, comparisons with the causes of the potential accidents and the actual accidents caused by human error were made and the results agreed approximately with the causes of the actual accidents.     

Accidents and accident prevention in agriculture a review of selected studies

Occupational accidents in agriculture are a problem all over the world. Farmers, family members and farm workers are facing risk; higher than in most other occupations. Methods for studies of accidents include statistical and epidermiological analyses, studies of safety attitudes and safety behavior, case studies, near-accident studies, motion and work experiments, interviews and a number of others. Many accidents involve the handling of animals in livestock buildings. In agricultural field work the tractor is often involved in accidents. Combine harvesters, feed processing machines and other types of equipment also cause a lot of injuries. In horticultural and forestry jobs the worker is exposed to considerable safety risks. There are obvious humanitarian reasons for making human work safer. In addition, accidents cost money and resources to the injured, to the employer and to the national economy as a whole. Prevention of accidents can be achieved by technical, human and organizational measures.     

汽车交通事故混沌分析及预测方法

提出一种新型的事故混沌理论.利用混沌理论和故障树法分析了汽车交通事故中的混沌特性,建立了基于事故混沌理论的汽车交通事故预测模型,并分析了预测模型的最大可预测尺度.该预测模型利用相空间近邻等距法对交通事故中的混沌吸引子进行预测,从而实现了对汽车交通事故的预测.仿真结果表明事故混沌理论对分析和预测汽车交通事故是有效的.     

交通事故的多维关联规则分析

城市机动车数量的增加已经导致城市交通事故的频繁发生，能否对已发生事故作出正确的分析将直接影响到能否对未来类似事故的成功避免。本文提出一种使用数据挖掘领域中的多维关联规则技术分析大量交通事故记录的方法，通过找出可能导致交通事故发生的频繁因素组合来发现某些事故发生的规律，并将这些规律作为现实中作出预防举措的依据。     

Multiple ergonomic interventions and transportation safety

This article discusses arguments and research evidence concerning multiple ergonomic approaches to problems of transportation safety. Transportation accidents ( and their consequences) are the result of multifactor processes. Therefore, the probability of an- accident ( and of an injury, given an accident) can be influenced by interventions directed at any of the factors. Furthermore, the most effective accident countermeasures are not necessarily those directed at the ‘ cause’ of accidents. As examples, multiple ergonomic countermeasures are noted for road accidents involving alcohol-intoxicated drivers and elderly drivers, as well as for minimizing injuries resulting from road accidents     

Human errors in fatal and serious occupational accidents in Finland

The aim of this study is to examine the effect of human error on industrial accidents. One hundred and seventy-eight fatalities and 99 serious accidents were classified according to Rasmussen's SRK model. Of accidents, 84-94% were due mainly to human error. Most of the errors were skill-based, next came rule-based errors and then knowledge-based errors. The type of error was analyzed by age, work experience and work tasks of the victims. The results showed that the SRK model is suitable for analyzing accidents in industrial work using rather simple technology.     

The relationship between safety climate and recent accidents: behavioral learning and cognitive attributions

OBJECTIVE: The association between accidents and subsequent work unit safety perceptions was assessed to address cognitive and behavioral changes following accidents. BACKGROUND: Many studies attempt to predict accident rates using measures of work unit safety, but effects vary considerably. Conversely, this study examined whether recent accidents may be positively associated with work unit safety perceptions, as suggested by behavioral learning mechanisms (increases in safety investments following accidents) or cognitive mechanisms (defensive attributions regarding accident causality). METHOD: Lagged squadron-level accident experience was correlated with work unit safety perceptions obtained through a 61-question safety climate survey administered to 6,361 individuals in U.S. Navy flight squadrons. RESULTS: Positive associations between minor or intermediately severe accidents and future safety climate scores were found, although no effect was found for major accidents. CONCLUSION: We suggest that accident history should be considered when examining work unit safety perceptions because recent accidents may be associated with higher safety climate scores. We did not find that this varies systematically with accident severity, and longitudinal research on additional samples is needed to further test this possibility. APPLICATION: This research may be used to refine measurement of work unit safety and to examine impacts of accidents or safety violations on workers' cognitive processes and group behavioral changes.     

Errors in routine driving tasks: a model and proposed analysis technique

Abstract

Models of behaviour and cognitive errors are briefly reviewed. A model derived from the work of Reason and Rasmussen is applied to the analysis of accidents at a crossroad in Friesland where the bulk of accidents occurred to drivers familiar with the location. Detailed application of the predicted error mechanisms to the steps of the driving task allows testable hypotheses to be formulated to differentiate between a number of possible causes of the accidents. The implications for research into accidents during routine driving tasks are discussed.     

Designing out accidents - first understand the problem

This paper describes a comprehensive accident data base which covers consumer products associated with accidents in and around the home. Each year data on some 50 000 to 60 000 cases distributed among 800 different products or features of the home are recorded and available for access. In addition to annual published summaries, analyses of specified data sub-sets are readily available. Such analyses can include case-listings which frequently provide considerable insight into the accidents. However, in more complex accidents these case listings may be inadequate, hence a facility has been incorporated in the data collection system to allow selected cases to be recontacted so that more details can be obtained and the product examined, if it is available. Two examples where this facility has been used (accidents involving tins and tin openers and accidents involving buggies) are discussed in relation to the methodologies involved and the preliminary results which have been obtained.     

DWI convictions linked to a higher risk of alcohol-related aircraft accidents

This paper assesses whether persons convicted of driving while intoxicated (DWI) are at increased risk of alcohol-related general aviation accidents. Past research has shown a clear link between DWI convictions and pilot-error accidents in commercial aviation. However, no study in the literature has addressed whether DWI convictions are associated with an increased risk of alcohol-related aircraft accidents. To evaluate a hypothesis, a total of 308912 pilot records over a 10-year period were analyzed using logistic regression. After potentially confounding variables were controlled, DWI convictions were found to be associated with alcohol-related aviation accidents. Pilots with DWI convictions were about 3.5 times more likely than pilots without convictions to have alcohol-related general aviation accidents. Actual or potential applications of this research include providing policy makers with data-driven information that is useful in improving decisions related to the medical certification of pilots.     

Automatic determination of traffic accidents based on KMC-based attribute weighting

In this study, the traffic accidents recognizing risk factors related to the environmental (climatological) conditions that are associated with motor vehicles accidents on the Konya-Afyonkarahisar highway with the aid of Geographical Information Systems (GIS) have been determined using the combination of K-means clustering (KMC)-based attribute weighting (KMCAW) and classifier algorithms including artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS). The dynamic segmentation process in ArcGIS9.0 from the traffic accident reports recorded by District Traffic Agency has identified the locations of the motor vehicle accidents. The attributes obtained from this system are day, temperature, humidity, weather conditions, and month of occurred traffic accidents. The traffic accident dataset comprises five attributes (day, temperature, humidity, weather conditions, and month of occurred traffic accidents) and 358 observations including 179 without accident and 179 with accident. The proposed comprises two stages. In the first stage, the all attributes of dataset have been weighted using KMCAW method. The aims of this weighting method are both to increase the classification performance of used classifier algorithm and to transform from linearly non-separable traffic accidents dataset to a linearly separable dataset. In the second stage, after weighting process, ANN and ANFIS classifier algorithms have been separately used to determine the case of traffic accidents as with accident or without accident. In order to evaluate the performance of proposed method, the classification accuracy, sensitivity, specificity and area under the ROC (Receiver Operating Characteristic) curves (AUC) values have been used. While ANN and ANFIS classifiers obtained the overall prediction accuracies of 53.93 and 38.76%, respectively, the combination of KMCAW and ANN and the combination of KMCAW and ANFIS achieved the overall prediction accuracies of 74.15 and 55.06% on the prediction of traffic accidents. The experimental results have demonstrated that the proposed attribute weighting method called KMCAW is a robust and effective data pre-processing method in the prediction of traffic accidents on Konya-Afyonkarahisar highway in Turkey.     

Prevention of accidents and injuries in Brazil

After the Second World War, Brazil went through a process of rapid industrialization: industries increased in size and new factories were built. Agriculture, started to diversify, and hand tools were replaced by machinery. As a result, a large number of new workers were needed. As their work tasks were unfamiliar and their training not good, work accidents and injuries at work increased. Statistical records of industrial accidents were started in 1969 and disclosed that in 1970 nearly 18% of industrial workers suffered accidents. A high proportion led to orthopaedic problems, 74-76% being back problems. Statistics for agricultural workers were not available, but a sample study in the state of Sao Paulo disclosed that 9-22% of workers suffered accidents, 54-65% by those working on sugar cane plantations. Preventive measures imposed by legislation were able to reduce these numbers and in 1984 the percentage of industrial workers suffering accidents fell to 3-84%. Legislation regarding the protection of workers from accidents is discussed and examples of the adopted preventive measures are presented.     

基于状态向量的危化品事故分析方法及应用

危险化学品行业属于高危险性行业,各类爆炸、火灾、泄漏和中毒事故时有发生.传统的基于因果关系的事故链分析方法受限于传统安全工程所依赖的技术基础和假定无法适应于今天所建造的复杂系统.本文以事故致因理论为基础,分析危化品事故形成的主要影响因素,构建了危化品事故状态向量,全面描述导致危化品事故发生的因素,并基于构建的状态向量进行危化品事故分析预测应用.利用高维向量对事故状态进行了定义,尽最大可能考虑了造成事故发生的众多因素,并利用支持向量机学习算法,建立事故预测模型.对已掌握的危化品事故进行的样本实验表明,本文提出的危化品事故预测方法,可有效快速的甄别事故状态,对危化品行业事故的预测预防具有积极意义.