道路因素对典型较严重道路交通事故严重性的影响分析

基于道路交通事故数据探究事故影响因素对于认识事故的影响因素、提高交通安全水平具有重要意义。利用近年来国内典型较严重道路交通事故数据,应用泊松模型和负二项模型,以区分事故形态的方式建立追尾事故、侧碰事故及撞行人事故的事故死亡率的道路影响因素分析模型。这些模型以三类事故中涉及人员的死亡数为因变量,以一系列道路因素为自变量,将事故涉及人数作为偏移变量。模型的具体形式以过离散系数及赤池信息量准则(AIC)为依据进行选择。结果显示,追尾事故的死亡率与道路等级、路侧防护设施显著相关;侧碰事故则与天气、路表情况、路口路段位置、坡度以及道路结构有关;撞行人事故与路表情况、道路等级、车道数、平曲线半径有关。本文拓展了事故严重性研究的深度,其研究成果对于更好地利用重特大事故的深入调查数据有现实意义,也可为事故分析及道路设计等提供借鉴。      

Using machine leaning techniques for evaluation of motorcycle injury severity

There is a growing interest in the application of the machine learning techniques in predicting the motorcycle crash severity. This is partly due to a progress in autonomous vehicles technology, and machine learning technique, which as a main component of autonomous vehicle could be implemented for traffic safety enhancement. Wyoming's motorcycle crash fatalities constitute a concern since the count of riders being killed in motorcycle crashes in 2014 was 11% of the total road fatalities in the state. The first step of crash reduction could be achieved through identification of contributory factors to crashes. This could be accomplished by using a right model with high accuracy in predicting crashes. Thus, this study adopted random forest, support vector machine, multivariate adaptive regression splines and binary logistic regression techniques to predict the injury severity outcomes of motorcycle crashes. Even though researchers applied all the aforementioned techniques to model motorcycle injury severities, a comparative analysis to assess the predictive power of such modeling frameworks is limited. Hence, this study contributes to the road safety literature by comparing the performance of the discussed techniques. In this study, Wyoming's motorcycle crash injury severities are modeled as functions of the characteristics that give rise to crashes. Before conducting any analyses, feature reduction was used to identify a best number of predictors to be included in the model. Also to have an unbiased estimation of the performance of different machine learning techniques, 5-fold cross-validation was used for model performance evaluation. Two measure, Area under the curve (AUC), and confusion matrix were used to compare different models' performance. The machine learning results indicate that random forest model outperformed the other models with the least misclassification and higher AUC. It was also revealed that a dichotomous response variable, with fatality and incapacitation injury in one category, along with all other categories in another group would result in a lower misclassification rate than a polychotomous response variable. This might result from the nature of motorcycle crashes, lacking a protection compared with passenger cars, preventing machine learning technique to get trained properly. Moreover, the most important variables identified by the random forest model are those related to the operating speed, resentful other party, traffic volume, truck traffic volume, riding under the influence, horizontal curvature, wide roadway with more than two lanes and rider's age.     

Developing a safer road user behaviour index

Road user behaviour is an essential factor of increasing the rate of traffic accidents worldwide. Road safety experts and scientists consider aspects of road users' behaviour to be the main risk factors for road fatalities. These factors include drinking alcohol, speeding, not wearing seat belts, not wearing helmets when riding two-wheeled vehicles, not using child restraints, consuming illegal drugs, and being distracted by mobile phone use. This paper aims to investigate the role of these factors in assessing the road user behaviour through aggregating them and build a composite indicator that can be used in countries benchmarking and cross countries comparison, then identifying most successful practises. To achieve this aim, data related to the selected indicators, life-saving rate, and real crash data were collected. The indicators were weighted using simple and theoretical methods. The weighted indicators were aggregated using simple additive method. The developed index was applied to 12 European countries to test the validation of the index through investigation the correlation between index’ ranking of countries with the ranking according to the rate of fatalities. It is concluded that the developed composite indicator can be used to assess the role of using the protection system and speeding in the severity of the road crashes. However, the role of the remaining factors in the likelihood of crashes occurrence needs more investigation. It can be concluded also that the road users' behaviour is not the only factor of reducing the road fatalities in some countries. This enhances the multidimensional system approach of defining the road safety. Based on this, it is recommended to consider other factors in conducting research, developing indices of road safety, and in recommending solutions. The results show also that the UK, Sweden, Ireland and Ireland have the most successful strategies to improve the road user behaviour among the selected countries; therefore, it is recommended to take lessons from these practices.     

基于GIS分析的深圳市道路交通事故空间分布特征研究

掌握城市道路交通事故空间分布特征是城市道路交通安全管理的重要基础。基于深圳市2014~2016年的道路交通事故数据,首先应用地理编码方法对原始事故记录进行空间定位,形成事故的空间分布。其次针对考虑/不考虑路网密度的2种情况,应用密度分析方法对道路交通事故多发的区域和事故严重程度较高的区域进行鉴别,比较2种情况下区域分布的差异并分析造成这种差异的可能原因。最后利用异常点分析和热点分析2种空间聚类分析模型对事故严重程度较高的区域进行进一步鉴别,并对密度分析和聚类分析2种方法得到的结果进行了比较。密度分析结果表明：就事故频度而言,深圳市中心城区单位面积上的交通事故频度较高,而郊区单位长度道路上的交通事故分布更为密集;就事故严重程度而言,郊区的交通事故平均严重程度高于市中心区域。造成上述差异的原因可能与郊区道路限速较高等因素有关。聚类分析结果与密度分析结果相近,在郊区形成了高严重程度的事故聚类,而在中心城区形成了低严重程度的事故聚类,说明郊区的交通事故严重程度总体高于市中心区域。从2种方法的比较来看,密度分析简单易行,有助于交通管理部门对城市交通事故空间分布特征直观快速的了解;聚类分析可精确到事故点,为精细化的交通安全管理工作提供支撑。研究结果表明基于密度分析和聚类分析的研究方法对于确定道路交通事故空间分布特征有良好的作用。     

Measure of productivity loss due to road traffic accidents in Thailand

As one of the top countries with the highest casualties per capita in road traffic accidents, Thailand needs to raise public awareness about the economic loss from road traffic crashes. This paper calculates the value of productivity loss due to road traffic accidents in Thailand in 2017. Extensive data collection and analyses enable to compute income losses over time in case of fatalities, permanent disabilities as well as major and minor injuries. The results reveal that, at the end of 2017, the total amount of productivity loss caused by road traffic accidents alone was approximately 121 billion Baht (45 billions for fatalities, 7 for disabilities, 67.5 for serious injuries and 1.5 for slight injuries), or close to 0.8% of the country's GDP, which is very significant. At-risk age groups are determined in each case and we see that the 16–25 age group is bearing the highest burden in all types of accidents. Future policies can then be targeted to types of casualties and to a specific public.     

Evaluation of risk factors for road accidents under mixed traffic: Case study on Indian highways

This paper presents an evaluation of risk factors for highway crashes under mixed traffic conditions. The basis of selecting study sites was abutting land use, roadway, and traffic characteristics. Accordingly, the study selected thirteen segments on the existing highway network in the state of West Bengal of India, covering a wide spectrum of such road attributes. A systematic investigation based on site-specific accident data to capture the highway sections' safety features revealed that the crash rate has steadily increased for years with traffic regardless of roadway category and conditions. A number of risk factors that affect road accidents were identified; they are mid-block access, pavement and shoulder conditions, vehicle involvement, time of day, and road configuration, i.e., two and multi-lane. The empirical observation indicates that the crash rate is relatively lower on multi-lane highways; however, the severity of any crash on such a road is relatively high. Notably, the crash frequencies on such roads are less during daylight hours due to the lane-based unidirectional traffic movement. This is quite the opposite during nighttime when drivers exhibit an inability to meet traffic contingencies, thereby increasing crash risk. The majority of crashes on two-lane highways are, on the other hand, due to unsafe driving manoeuvers. The study also observed that frequent mid-block accesses and poor shoulder conditions reduce scopes to rectify driving errors and increase crash risk as a consequence. The paper subsequently suggests proactive approaches to identify safety deficits at the time of planning and designing.     

Future of road safety and SDG 3.6 goals in six Indian cities

In this paper, we use estimates of the effectiveness of existing road safety technologies and interventions to estimate the reduction in road safety deaths in six Indian cities over the next decade, in order to achieve the SDG 3.6 goal of a 50% reduction by 2030. Only the existing interventions are considered and technologies that might be available in the future are not accounted for. The results show that similar policies for all cities will not produce the same results, and that achieving the SDG 3.6 goal does not automatically reduce fatality rates in cities with high fatality rates. The introduction of safer cars with currently available safety technologies, although necessary, will have much less effect than the combined effect of motorcycle safety technologies, speed control and traffic calming. This study suggests that while SDG 3.6 targets may be satisfied by 2030 with great effort in India, the presently available safety interventions may not be adequate to bring about death rates below 2.0 per hundred thousand persons. Since the situation differs significantly between cities, it will be important to evolve city-specific policies for safety intervention priorities and changes in travel behavior. The desired reduction in road traffic injuries in India will not be possible without much greater investment in road safety research and road design for safer travel.     

Exclusive motorcycle lanes: A systematic review

Road accidents are the main leading cause of death, and more than half of people killed in road accidents are motorcyclists, pedestrians, and bicyclists. In developing countries, the share of motorcycles is very high in the traffic stream, which results in an increased number of accidents. Nonetheless, a high share of motorcycles and risky riding behavior of motorcyclists raise notable threats to other road users as well as themselves. Segregating motorcycles from the main traffic stream by providing an Exclusive MotorCycle Lane (EMCL) is reported as one of the strategies to improve motorcyclist's safety and overall road safety. Although EMCLs are successfully running in some Asian countries like Malaysia, Taiwan, and Indonesia, and have reported reducing motorcycle accidents, existing literature related to such lanes is limited and lacks combined contemplation of various design factors. Therefore, a systematic review of studies related to EMCL was carried out in the present paper using the PRISMA approach. The review was majorly divided into the following three categories viz., geometric design elements of EMCL, motorcyclist's flow characteristics on EMCL, and traffic control measures for EMCL to highlight the research lacunas in this field. The present study aims to cast light on the need for specific geometric design standards for EMCL and to assess the safety impact of segregating motorcyclists from other mixed traffic. The review highlights that the design standards for EMCL should be based on the motorcycle's characteristics, as it varies from other vehicle categories in terms of riding behavior and the physical properties of the motorcycle.     

Road characteristics and environment factors associated with motorcycle fatal crashes in Malaysia

This study aims to determine risk factors contributing to traffic crashes in 9,176 fatal cases involving motorcycle in Malaysia between 2010 and 2012. For this purpose, both multinomial and mixed models of motorcycle fatal crash outcome based on the number of vehicle involved are estimated. The corresponding model predicts the probability of three fatal crash outcomes: motorcycle single-vehicle fatal crash, motorcycle fatal crash involving another vehicle and motorcycle fatal crash involving two or more vehicles. Several road characteristic and environmental factors are considered including type of road in the hierarchy, location, road geometry, posted speed limit, road marking type, lighting, time of day and weather conditions during the fatal crash. The estimation results suggest that curve road sections, no road marking, smooth, rut and corrugation of road surface and wee hours, i.e. between 00.00 am to 6 am, increase the probability of motorcycle single-vehicle fatal crashes. As for the motorcycle fatal crashes involving multiple vehicles, factors such as expressway, primary and secondary roads, speed limit more than 70 km/h, roads with non-permissible marking, i.e. double lane line and daylight condition are found to cause an increase the probability of their occurrence. The estimation results also suggest that time of day (between 7 pm to 12 pm) has an increasing impact on the probability of motorcycle single-vehicle fatal crashes and motorcycle fatal crashes involving two or more vehicles. Whilst the multinomial logit model was found as more parsimonious, the mixed logit model is likely to capture the unobserved heterogeneity in fatal motorcycle crashes based on the number of vehicles involved due to the underreporting data with two random effect parameters including 70 km/h speed limit and double lane line road marking.     

Quantification of surrogate safety measure to predict severity of road crashes at median openings

Traffic safety assessment is an integral part of transportation engineering. In a developing country like India, it is observed that in every four second, one person gets injured in road crashes. Moreover, at median openings which are usually uncontrolled in India, the severity of road crashes increase many fold. This is due to the fact that neither lane discipline nor priority rule is followed at the median openings. Conventionally, road crash data reports were used to study and analyze traffic safety. However, the drawback of this traditional method is that a lot of accidents need to be recorded for analysis and to draw any conclusions and take necessary corrective measures. In developing countries like India, available accident data are based on reports submitted by the police department of respective state governments. The accuracy of these accident data details is highly questionable. Therefore, in the recent times surrogate traffic safety measures are being used to analyze traffic safety. Various surrogate traffic measures like Deceleration Time (DT), Time to Collision (TTC), Post Encroachment Time (PET), etc. are being used to examine road safety. These values are based on the temporal and spatial proximity between road-users during possible conflict situation. Among all the traffic safety measures, PET is regarded as the most reliable and most commonly used indicator. Therefore, in this study, PET across different traffic volume levels at median opening area is calculated. A critical safe ratio has been introduced to better analyze the traffic safety at median opening based on minimum stopping sight distance (SSD) as per IRC: 66–1976 and speed to PET ratio. Finally clustering technique has been used to define various severity indices for probable road crashes at median opening area. For this study, data has been collected from different median openings located on six-lane divided urban roads.     

Impacts of accident severity factors and loss values of crashes on expressways in Thailand

The number of road accidents and the level of accident severity have been extensively applied as the indicators for measuring the efficiency of service provision in road network systems of each country. This research utilized accident data on expressway networks during B.E.2550 (2007) to B.E.2553 (2010) (updated data was collected), in which Expressway Authority of Thailand (EXAT) as legislatively mandated unit has taken responsibility for the execution of nine expressway routes covering distances totaling over 207 km with a record of 2194 crashes. The chief objective of the study aims to forecast the accident severity through formulating Multiple Logistic Regression Model to analyze the probability of injury accident and fatal accident in comparison with property damage only accident. Its measurement comprehensively considers statistical relationship among variables such as average speed on road section, average traffic volume per day, period of time, weather conditions, physical characteristics of accident area, and causes of accident. Together, the research question is to verify whether these variables affect the opportunity or probability of three levels of accidents and investigate impacts of accident loss values due to the reduction in crash severity measures.     

车速与交通事故综合研究

随着人们对交通安全问题日益关注,道路交通安全技术和相关研究也得以快速发展。分析车速对交通事故率及事故严重程度的影响,建立车速与交通事故率和事故严重程度2者之间的相关关系。研究发现,车速偏差越大,事故率越高;事故冲撞前后车速变化越大,事故越严重。由此可知,车速对交通安全有显著影响。     

Motorcycle fatalities in Malaysia

Malaysia has the highest road fatality risk (per 100,000 population) among the ASEAN countries and more than 50% of the road accident fatalities involve motorcyclists. This study has collected and analysed data from the police, government authorities, and national and international research institutes. Only fatality data are used due to the severe underreporting of severe injuries (up to 600%) and slight injuries (up to 1400%). The analysis reveals that the highest numbers of motorcycle fatalities occur in rural locations (61%), on primary roads (62%) and on straight road sections (66%). The majority are riders (89%), 16 to 20 years old (22.5%), and 90% of the motorcycles are privately owned. Of those involved in fatal accidents, 75% of the motorcyclists wear helmets, and 35% do not have proper licences. The highest number of fatalities by type of collision is ‘angular or side’ (27.5%). Although fatal motorcyclist crashes mostly involve ‘passenger cars’ (28%), motorcyclists are responsible for 50% of the collisions either by crashing singly (25%) or with other motorcyclists (25%). While male motorcyclists predominate (94% of fatalities), female motorcyclists aged 31 to 70, possessing ‘no licence’, not wearing helmets and travelling during the day, account for a higher percentage than male motorcyclists. Malaysia must acquire more motorcycle exposure data and establish an injury recording system and database based on hospital-records. To reduce motorcycle fatalities, it first has to understand why young male motorcyclists are prone to fatal crashes in the evenings and on weekends on rural primary roads, especially on straight road sections.     

Effectiveness of enforcement resources in the highway patrol in reducing fatality rates

Motor vehicle crashes are a leading cause of death in the United States. Wyoming initiated a safety study to investigate the underlying causes of high crash rates since it has one of the highest fatality rates in the nation. Research has shown relationships between increased enforcement activity and road crash/fatality reduction. However, little research has attempted to quantitatively measure the impact of various forms of police enforcement, such as the percentage of enforcement time and the quantity of resources, on fatality rate. Therefore, this study was set forward to fill this gap. Data from the highway patrol in Wyoming and the surrounding states were used in this study. Although Wyoming and these nearby states have very similar features in terms of geography and weather, they are different in terms of road mileage and traffic. Therefore, the data was normalized based on highway mileage and miles traveled. Enforcement efforts were compared in terms of allocated enforcement budget, number of sworn officers, and time spent patrolling. The results indicated that there are negative relationships between fatality rate and budget, number of officers, and active hours on the field. This paper also investigated which variable is the best predictor of fatality rate. The results indicated that time spent on the field by highway patrol officers is the best indicator of fatality rate. It was found that although some states like Wyoming have a higher number of sworn officers, they spend less time actively enforcing highway safety. This study provides information needed for authorities to allocate more funding to the highway patrol, and for the highway patrol to spend more time on the road.     

车种分流影响道路交通事故之灰关联分析

台湾地区近年致力于交通安全改善之相关执行计划,企图透过教育、工程与执法之3E手段来降低交通事故数量与严重程度,然而思考如何将机动车分流落实到工程改善手段中亦是思考重点之一,而此分流措施必须奠基于有无采取机动车分流与机动车事故数量则是必须具备高度相关才有落实之可行性.因此,透过灰关联分析探讨台湾地区彰化市5条道路之基础设施与机动车事故的关联程度,其中路肩宽度与障碍物,以及机动车分流长度之灰关联度均为影响机动车事故的重要因素,因此考量是否有采行机动车分流措施则是与交通安全有绝对关系,未来则可依据事故类型加以评估是否落实机动车分流措施.      

山区高速公路隧道路段与开放路段的事故影响因素分析

高速公路隧道构造特殊且通行环境复杂,因而通常事故多发。为探究高速公路隧道路段与开放路段事故影响因素和严重程度致因机理的差异,采集沪昆高速邵怀段2011—2016年期间1 537起事故为研究样本;以事故发生路段为响应变量构建逻辑回归模型,解释各种风险因素对事故发生路段倾向性的影响差异;分别针对隧道路段与开放路段建立模型研究事故伤害严重程度的影响因素。建立二元Logit回归模型分析事故的发生倾向性和2类路段的事故严重程度的影响因素;采用随机参数Logit模型以反映异质性条件对参数的影响。统计表明:与疲劳驾驶、未保持安全距离相关的事故发生在隧道路段的概率更高,其事故发生概率分别是开放路段的2.373和2.482倍;与隧道路段事故严重程度正相关的因素包括下坡（坡度2%以上）、夏季和超速行驶,其中下坡（坡度2%以上）段的严重事故发生的概率为上坡（坡度2%以上）的3.397倍,夏季的严重事故发生概率为秋季的3.951倍,超速行驶相关的严重事故发生概率为其他不当驾驶行为的4.242倍;与开放路段事故严重程度正相关的因素包括超速行驶和疲劳驾驶,其中超速行驶相关的严重事故概率是其他不当驾驶行为的2.713倍,疲劳驾驶相关的严重事故概率是其他不当驾驶行为的4.802倍。研究表明,山区高速公路隧道路段与开放路段的事故发生概率及其严重程度的影响因素存在一定的差异性,研究结论可为山区高速公路差异管理方案制定提供依据。      

Exploring factors contributing to injury severity at work zones considering adverse weather conditions

Despite recent efforts to improve work zone safety, the frequency and severity of crashes at work zones are still considerably high. The effect of work zones on traffic safety can be exacerbated by adverse weather conditions. As an example, a sudden reduction in visibility may intensify the severity of work zone crashes. There is a lack of studies that strive to gain a good understanding of the effect of weather on the severity of work zone crashes. In this study, an Ordered Probit Model was developed to identify factors affecting the severity of work zone crashes in different spatial, temporal, and environmental conditions in Washington state using five-year of work zone-related crashes (2009–2013). The interesting findings of this study showed that weather and lighting conditions are among the most important factors influencing the severity of crashes at work zones. Lack of daylight was found to be a determining factor in increasing the severity of work zone crashes, specifically, during dusk and dawn. It was also found that although drivers have less severe work zone-related crashes in adverse weather conditions, the interactions between adverse weather conditions and other contributing factors might increase the severity of work zone crashes. The results of this study will help traffic engineers to design effective safety countermeasures considering different contributing factors including the weather and lighting conditions in the work zone planning and installation stages to prevent safety deficiencies.     

Education influence in traffic safety: A case study in Vietnam

It is well known that traffic accidents are of high importance to the public health spectrum around the world. Moreover, in developing countries such as Vietnam, the mortality rate from road traffic accidents is rather high in comparison with other Southeast Asian countries. Not only do the majority of the people killed and seriously injured significantly affect the quality of life of the citizens, but traffic accidents also negatively impact a nation's economic and social development. Statistics show that far more people are injured or die in traffic accidents than are afflicted by any of the most serious diseases. The very high occurrence of traffic accidents in Vietnam has become one of the country's major social issues. The importance of human factors in transport policy discussion is growing. There is a realization that policy options that appear beneficial in principle have to be checked for their feasibility of implementation. Understanding and describing driver behavior become a challenge when one tries to identify driver errors in determining accident/conflict causal factors and countermeasures.In recent years, having understood the serious effects of traffic accidents on society at large, scientific researchers, traffic engineers and policy makers in Vietnam have developed many projects and conducted research in the field of traffic safety. The human factor is also considered to be the central element in the whole system. The final goal is to organize a traffic environment that is convenient and safe for road users.This article explains the application of the risk analysis approach in evaluating influences of education and enforcement in traffic safety.     

基于随机参数Logit模型的校车事故伤害严重程度分析

为深入分析安全因素对校车事故伤害严重程度的影响，探寻事故数据中未观察到的异质性，基于随机参数Logit模型从驾驶员、车辆、道路特征及环境4个方面构建校车事故伤害严重程度模型。结果表明:①涉事车辆数为2辆且对应参数服从正态分布时，不发生死亡受伤事故的概率为83.84%；②驾驶员年龄35~44岁、涉事车辆数为1辆时，死亡受伤事故概率均降低0.58%；③道路限速值为40~50 km/h时发生死亡受伤事故概率增加0.35%，道路限速值大于60 km/h时发生死亡受伤事故概率增加0.96%；④安全气囊状态打开，死亡受伤事故概率增加2.35%；⑤交通控制方式为车道标线时可能伤害事故概率增加1.85%，控制方式为中央分隔带时未受伤事故概率降低1.44%，死亡受伤事故发生概率却增加0.48%；⑥不安全时倒车转弯时发生可能伤害事故概率降低0.42%，分心驾驶、未按规定车道行驶、跟车太近和其他（饮酒）时未受伤事故概率分别增加1.36%，0.56%，0.39%和0.97%，可能受伤事故和死亡受伤事故发生概率却有所降低。      

Education influence in traffic safety: A case study in Vietnam

It is well known that traffic accidents are of high importance to the public health spectrum around the world. Moreover, in developing countries such as Vietnam, the mortality rate from road traffic accidents is rather high in comparison with other Southeast Asian countries. Not only do the majority of the people killed and seriously injured significantly affect the quality of life of the citizens, but traffic accidents also negatively impact a nation's economic and social development. Statistics show that far more people are injured or die in traffic accidents than are afflicted by any of the most serious diseases. The very high occurrence of traffic accidents in Vietnam has become one of the country's major social issues. The importance of human factors in transport policy discussion is growing. There is a realization that policy options that appear beneficial in principle have to be checked for their feasibility of implementation. Understanding and describing driver behavior become a challenge when one tries to identify driver errors in determining accident/conflict causal factors and countermeasures.In recent years, having understood the serious effects of traffic accidents on society at large, scientific researchers, traffic engineers and policy makers in Vietnam have developed many projects and conducted research in the field of traffic safety. The human factor is also considered to be the central element in the whole system. The final goal is to organize a traffic environment that is convenient and safe for road users.This article explains the application of the risk analysis approach in evaluating influences of education and enforcement in traffic safety.