汽车防撞系统测距技术的研究

为防止汽车与前方物体发生碰撞，使汽车始终在安全车速下行驶，减少事故的发生，从而达到有效预防追尾碰撞事故发生的目的，本文介绍了汽车防碰撞系统的基本原理，并比较了各种测距技术的优缺点，对于提高我国道路交通的安全，降低交通事故发生率，促进我国智能交通系统的发展具有重要意义。     

基于V2V无线通讯协议高速公路追尾防撞系统

每年,超过23%的交通事故是由机动车追尾碰撞造成的。这里提供了一种可以降低追尾事故发生几率的机动车之间(V2V)的无线通讯协议。本文提出并研究了一种能够为在高速公路上行使的机动车之间传播警告信息的基于MAC协议的802.11标准。设计此标准的目的是能够确保在低延时的情况下接收到警告消息,从而使驾驶员可以有足够的时间采取相应措施来避免追尾事故的发生。     

简议架线电机车行车追尾的安全报警装置

随着架线电机车的广泛应用，其安全运营越来越重要。本文针对架线电机车行车追尾事故的经常发生，探讨了利用架线和铁轨传输信号，采用两个不同频率的音频信号，分别对不同两个频率的载波信号进行调频，用于双行线路的同方向运行的两台架线电机车进行追尾报警的安装装置。     

事故树图形的计算机辅助绘制算法研究

提供了一种有效的算法,根据输入的各种事件的基本信息及其因果逻辑关系,利用树的深度优先遍历后序算法,实现事故树的自动绘制,体现事故树模型分析形象、直观、明了的特点.该算法能即时计算出事故树顶事件发生的概率、最小割集、概率重要度、关键重要度等参数,为对事故树进行定性、定量分析提供强有力的图形和数据支持.     

事故树在炸药库管理上的应用

炸药库爆炸事故的频频发生,给国家带来了巨大损失.结合实例,采用事故树分析法(FTA)对某炸药库的爆炸事件作了定性分析,确定了引起项上事件的各个基本事件,构造了事故树和成功树,计算得出22个最小割集和5个最小径集,找出发生爆炸事故的可能原因和主要影响因素,并根据分析结果指出炸药库在管理上存在的缺陷,提出了相应的安全管理措施.对实施炸药库的安全管理具有参考价值.     

受限空间作业中毒窒息事故分析与预防

根据某化工企业受限空间作业中毒窒息事故的典型案例,分析引起设备内受限空间作业中毒窒息事故发生的各种原因,运用事故树分析法分析了引起受限空间作业中毒窒息事故的基本原因,对事故树进行了最小割集和最小径集的计算,分析了各基本事件的结构重要度.根据分析的结果,从技术、管理和操作等方面,提出了防止受限空间作业中毒窒息事故发生的措施.     

硝铵炸药真空干燥工艺燃爆事故致灾因素的研究

真空干燥是硝铵炸药生产过程中一道容易发生燃爆事故的重要工序。为研究硝铵炸药真空干燥过程中发生燃爆事故的原因及机理，通过事故案例分析和现场调研，确定了导致燃爆事故的各个基本事件及其逻辑关系，并由此构建以燃爆事故作为顶事件的事故树。采用布尔代数化简事故树，得到87个最小割集和9个最小径集，结果显示每个最小径集包含的基本事件都较多，说明真空干燥工艺安全性较低。通过计算各基本事件的结构重要度并排序，得到结构重要度较大的基本事件，由此推断出导致燃爆事故的主要基本事件，并有针对性地提出相应的改进措施与建议，为企业的安全生产提供参考。     

爆破飞石产生原因事故树分析

为了避免爆破飞石伤人事故的发生,确保爆破安全,根据现场调研,运用安全分析理论查找爆破飞石产生的原因,为爆破作业设计、施工和安全管理提供科学依据。运用事故树分析法FTA(fault tree analysis)对某一爆破飞石伤人事故进行全面、系统的分析,确定引起顶上事件发生的因素,提出相应的预防措施。     

如何提高汽车安全性中雷达系统的应用

为保障汽车驾驶时的舒适性和安全性，世界各国对汽车防撞技术的研究和发展投入了大量的人力，物力和财力。据统计，危险境况时，如果能给驾驶负半秒钟的预处理时间，则可分别减少追尾事故的30％，路面相关事故的50％，迎面撞车事故的60％，所以现代汽车安装各类雷达系统以保障行车安全。     

事故树分析法在煤矿事故调查中对责任者责任重要度定量分析评价的应用

事故树分析法也称故障树分析法（Fault Tree Analysis简称FTA），是安全系统工程的重要分析方法之一。此法不仅可以定性了解事件动态变化的过程，还可以定量的计算各种状态的发生概率，并根据所取得的结果与预定的目标值进行比较验证，分析出各基本事件重要度系数，具体应用到煤矿事故调查中，可以对事故责任认定结果进行理论检验。     

Evaluation of rear-end crash risk at work zone using work zone traffic data

This paper aims to evaluate the rear-end crash risk at work zone activity area and merging area, as well as analyze the impacts of contributing factors by using work zone traffic data. Here, the rear-end crash risk is referred to as the probability that a vehicle is involved in a rear-end crash accident. The deceleration rate to avoid the crash (DRAC) is used in measuring rear-end crash risk. Based on work zone traffic data in Singapore, three rear-end crash risk models are developed to examine the relationship between rear-end crash risk at activity area and its contributing factors. The fourth rear-end crash risk model is developed to examine the effects of merging behavior on crash risk at merging area. The ANOVA results show that the rear-end crash risk at work zone activity area is statistically different from lane positions. Model results indicate that rear-end crash risk at work zone activity area increases with heavy vehicle percentage and lane traffic flow rate. An interesting finding is that the lane closer to work zone is strongly associated with higher rear-end crash risk. A truck has much higher probability involving in a rear-end accident than a car. Further, the expressway work zone activity area is found to have much larger crash risk than arterial work zone activity area. The merging choice has the dominated effect on risk reduction, suggesting that encouraging vehicles to merge early may be the most effective method to reduce rear-end crash risk at work zone merging area.     

Utilizing the eigenvectors of freeway loop data spatiotemporal schematic for real time crash prediction

The concept of crash precursor identification is gaining more practicality due to the recent advancements in Advanced Transportation Management and Information Systems. Investigating the shortcomings of the existing models, this paper proposes a new method to model the real time crash likelihood based on loop data through schematic eigenvectors. Firstly, traffic volume, occupancy and density spatiotemporal schematics in certain duration before an accident occurrence were constructed to describe the traffic flow status. Secondly, eigenvectors and eigenvalues of the spatiotemporal schematics were extracted to represent traffic volume, occupancy and density situation before the crash occurrence. Thirdly, by setting the vectors in crash time as case and those at crash free time as control, a logistic model is constructed to identify the crash precursors. Results show that both the eigenvectors and eigenvalues can significantly impact the accident likelihood compared to the previous study, the proposed model has the advantage of avoiding multicollinearity, better reflection of the overall traffic flow status before the crash, and improving missing data problem of loop detectors.     

Time and distance to first accident and driving patterns of young drivers with pay-as-you-drive insurance

We conducted a study of approximately 16,000 drivers under the age of 30 that had purchased a pay-as-you-drive insurance policy, where their risk of being involved in a crash was analyzed from vehicle tracking data using a global positioning system. The comparison of novice vs. experienced young drivers shows that vehicle usage differs significantly between these groups and that the time to the first crash is shorter for those drivers with less experience. Driving at night and a higher proportion of speed limit violations reduces the time to the first crash for both novice and experienced young drivers, while urban driving reduces the distance traveled to the first crash for both groups. Gender differences are also observed in relation to the influence of driving patterns on the risk of accident. Nighttime driving reduces the time to the first accident in the case of women, but not for men. The risk of an accident increases with excessive speed, but the effect of speed is significantly higher for men than it is for women among the more experienced drivers.     

Driving performance assessment: effects of traffic accident location and alarm content

According to accident statistics for Taiwan, the two most common traffic accident locations in urban areas are roadway segments and intersections. On roadway segments, most collisions are due to drivers not noticing the status of leading vehicle. At intersections, most collisions are due to the other driver failing to obey traffic signs. Using a driving simulator equipped with a collision warning system, this study investigated driving performance at different accident locations and between different alarm contents, and identified the relationship between crash occurrences and driving performance. Thirty participants, aged 20-29 years, were recruited in this study. Driving performance measures were perception-reaction time, movement-reaction time, speed and a crash. Experimental results indicated that due to different demands for processing information under different traffic conditions, driving performance differed at the two traffic accident locations. On a roadway segment, perception-reaction time for a beep was shorter than the time for a speech message. Nevertheless, at an intersection, a speech message was a great help to drivers and, thus, perception-reaction time was effectively reduced. In addition, logistic regression analysis indicates that perception-movement time had the greatest influence on crash occurrence.     

Accident prediction model for railway-highway interfaces

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.     

Evaluating the risk from depleted uranium after the Boeing 747-258F crash in Amsterdam, 1992

On 4 October 1992, a large cargo plane crashed into an apartment building in the Bijlmermeer quarter of Amsterdam. In the years following the accident, an increasing number of people started reporting health complaints, which they attributed to exposure to dangerous substances after the crash. Since the aircraft had been carrying depleted uranium as counterbalance weights and about 150 kg uranium had been found missing after clearance of the crash site, exposure to uranium oxide particles was pointed out as the possible cause of their health complaints.Six years after the accident, a risk analysis was therefore carried out to investigate whether the health complaints could be attributed to exposure to uranium oxide set free during the accident. The scientific challenge was to come up with reliable results, knowing that - considering the late date - virtually no data were available to validate any calculated result. The source term of uranium was estimated using both generic and specific data. Various dispersion models were applied in combination with the local setting and the meteorological conditions at the time of the accident to estimate the exposure of bystanders during the fire caused by the crash. Emphasis was given to analysing the input parameters, inter-comparing the various models and comparing model results with the scarce information available.Uranium oxide formed in the fire has a low solubility, making the chemical toxicity to humans less important than the radiotoxicity. Best-estimate results indicated that bystanders may have been exposed to a radiation dose of less than 1 microSv, whereas a worst-case approach indicated an upper limit of less than 1 mSv. This value is considerably less than the radiation dose for which acute effects are to be expected. It is therefore considered to be improbable that the missing uranium had indeed led to the health complaints reported.     

A disaggregate approach to crash rate analysis

This paper presents a disaggregate approach to crash rate analysis. Enumerating crash rates on a per trip-kilometer basis, the proposed method removes the linearity assumption inherent in the conventional quotient indicator of accidents per unit travel distance. The approach involves combining two disparate datasets on a geographic information systems (GIS) platform by matching accident records to a defined travel corridor. As an illustration of the methodology, travel information from the Victorian Activity and Travel Survey (VATS) and accident records contained in CrashStat were used to estimate the crash rates of Melbourne residents in different age-sex groups according to time of the day and day of the week. The results show a polynomial function of a cubic order when crash rates are plotted against age group, which contrasts distinctly with the U-shape curve generated by using the conventional aggregate quotient approach. Owing to the validity of the many assumptions adopted in the computation, this study does not claim that the results obtained are conclusive. The methodology, however, is seen as providing a framework upon which future crash risk measures could be based as the use of spatial tracking devises become prevalent in travel surveys.     

Analyzing the influence of median cross-section design on highway safety using vehicle dynamics simulations

Although vehicle dynamics simulations have long been used in vehicle design and crash reconstruction, their use for highway design is rare. This paper investigates the safety of highway medians through iterative simulations of off-road median encroachments. The commercially available software CarSim was used to simulate over one hundred thousand encroachments, representing the entire passenger vehicle fleet and a wide range of encroachment angles, departure speeds, steering inputs, and braking inputs. Each individual simulation output was then weighted using data from previous studies to reflect the probability of each specific accident scenario occurring in a real-life median encroachment. Results of this analysis illustrate the relative influence of median cross-section geometry on the resulting accident outcomes. The simulations indicate that the overall safety of a highway median depends on the occurrence of both vehicle rollover and median crossover events, and the cross-section shape, slope, and width are all shown to greatly affect each of these incidents. An evaluation of the simulation results was conducted with vehicle trajectories from previous experimental crash tests. Further assessment of the aggregate simulation results to actual crash data was achieved through comparison with several databases of crash statistics. Both efforts showed a strong agreement between the simulations and the real-life crash data.     

An evaluation of responsibility analysis for assessing alcohol and drug crash effects

This paper evaluates judgments of driver crash responsibility to estimate alcohol and drug impairment effects when exposure data are unavailable to calculate crash risks. Previous studies using responsibility judgments provided some evidence that responsibility is related to BAC. Other studies, some inferring responsibility, indicated a relation between responsibility and relative crash risk. Data are presented showing that responsibility judgments with a rating scale have high interrater reliability, and systematic relations with BAC suggest some validity in the ratings. A method is demonstrated for estimating relative crash risk from responsibility judgments with accident data, and the limitations of responsibility analysis are discussed. While alcohol and drug impairment effects are best determined with relative crash risks determined from accident and exposure data. responsibility analysis may provide useful indications in the absence of exposure data.     

Drug use and the severity of a traffic accident

Several studies have showed that driving under the influence of alcohol and/or certain illicit or medicinal drugs increases the risk of a (severe) crash. Data with respect to the question whether this also leads to a more severe accident are sparse. This study examines the relationship between the use of alcohol, illicit drugs and/or medicinal drugs and the severity of an accident within a group of drivers that were involved in a crash in The Netherlands. Blood samples of 993 drivers, collected in the period from October 1998 through September 1999, were linked to accident characteristics as available from the National Transport Research Centre. The outcome measure was the severity of the accident. An accident was considered severe when the accident had resulted in hospital admission or death. All the blood samples obtained after the accident were screened for the presence of alcohol, illicit drugs (opiates, amphetamines and amphetamine-like substances, cocaine and metabolites, methadone, cannabinoids) and medicinal drugs (benzodiazepines, barbiturates and tricyclic antidepressants). The strength of the associations between exposure to the different classes of alcohol/drugs/medicines and the severity of the accident was evaluated using logistic regression analysis and were expressed as odds ratios (OR), adjusted for age, gender, time of the day, day of the week and urban area. The most frequently detected drugs were cannabinoids, benzodiazepines and cocaine. Our results showed no clear association between the use of alcohol, illicit drug and/or medicinal drug use and the severity of the accident. Given the process of obtaining blood samples from drivers involved in accidents and the retrospective nature of the study, we cannot rule out the occurrence of selection bias. Therefore, our findings need further confirmation.