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.     

疲劳驾驶交通事故的严重程度影响因素分析

为探究和定量分析疲劳驾驶交通事故严重程度的影响因素,以广东省1370条疲劳驾驶事故数据为基础,对比分析不同年份、时间段以及年龄段的疲劳驾驶交通事故特征;以交通事故严重程度为因变量,将其分为严重事故和非严重事故,从驾驶员年龄、驾龄、车辆类型等17个初步选择的自变量中筛选对疲劳驾驶交通事故严重程度具有显著影响的因素;采用二...     

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.     

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.     

Understanding factors associated with misclassification of fatigue-related accidents in police record

IntroductionFatigue is one of the riskiest causes of traffic accidents threatening road safety. Due to lack of proper criteria, the identification of fatigue-related accidents by police officers largely depends on inferential evidence and their own experience. As a result, many fatigue-related accidents are misclassified and the harmfulness of fatigue on road safety is misestimated.MethodIn this paper, a joint model framework is introduced to analyze factors contributing to misclassification of a fatigue-related accident in police reports. Association rule data mining technique is employed to identify the potential interactions of factors, and logistic regression models are applied to analyze factors that hinder police officers' identification of fatigue-related accidents. Using the fatigue-related crash records from Guangdong Province during 2005–2014, factors contributing to the false positive and false negative detection of the fatigue-related accident have been identified and compared.ResultsSome variables and interactions were identified to have significant impacts on fatigue-related accident detection.ConclusionsBased on the results, it can be inferred that the stereotype of certain groups of drivers, crash types, and roadway conditions affects police officers' judgment on fatigue-related accidents.Practical applicationsThis finding can provide useful information for training police officers and build better criteria for fatigue identification.     

Situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds in Japan

Abstract

Objective: This study aimed to investigate the situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds in Japan. We focused on vehicles with 4 or more wheels. Such characteristics included daytime or nighttime conditions, road type, vehicle behaviors preceding the accident, and vehicle impact locations.

Methods: Pedestrian fatality data on vehicle–pedestrian accidents were obtained from the Institute for Traffic Accident Research and Data Analysis of Japan (ITARDA) from 2005 to 2014. Nine vehicle classifications were considered: Trucks with gross vehicle weight (GVW) ≥7.5 tons and <7.5 tons, buses, box vans, minivans, sport utility vehicles (SUVs), sedans, light passenger cars (LPCs), and light cargo vans (LCVs). We compared the situational daytime or nighttime conditions, road type, vehicle behaviors preceding the accident, and vehicle impact locations for accident-involved vehicles traveling at low and higher speeds across all vehicle types.

Results: The results indicate that pedestrian fatalities involving vehicles traveling at low speeds occurred more often under daytime conditions across all vehicle types. At signalized intersections, the relative proportions of pedestrian fatalities were significantly higher when vehicles were traveling at low speed, except when the accidents involved box vans or SUVs. Similarly, when vehicles turned right, the relative proportions of pedestrian fatalities were significantly higher when vehicles traveling at low speed were involved across all vehicle types. In terms of the frontal right vehicle impact location, the relative proportions of pedestrian fatalities were significantly higher when trucks with GVW ≥7.5 tons or <7.5 tons, sedans, or LCVs traveling at low speed were involved.

Conclusions: The situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds identified in this study can guide targeted development of new traffic safety regulations or technologies specific to vehicle–pedestrian interactions at low vehicle travel speeds (i.e., driver alert devices or automated emergency braking systems). Ultimately, these developments can improve pedestrian safety by reducing the frequency or severity of vehicle–pedestrian accidents for vehicles turning right at intersections and/or reducing the number of resultant pedestrian fatalities.     

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。     

A case study analysis to examine motorcycle crashes in Bogota,Colombia

IntroductionContributory factors to motorcycle crashes vary among populations depending on several aspects such as the users' profiles, the composition and density of traffic, and the infrastructure features. A better understanding of local motorcycle crashes can be reached in those places where a comprehensive analysis is performed. This paper presents the results obtained from a case study analysis of 400 police records of accidents involving motorcycles in Bogota.MethodTo achieve a deeper level of understanding of how these accidents occur, we propose a systemic approach that uses available crash data. The methodology is inspired by accident prototypical scenarios, a tool for analysis developed in France.ResultsWhen grouping cases we identified three categories: solo motorcycle accidents, motorcyclist and pedestrian accidents, and accidents involving a motorcycle and another vehicle. Within these categories we undertook in-depth analyses of 32 groups of accidents obtaining valuable information to better comprehend motorcyclists' road crashes in a local context. Recurrent contributory factors in the groups of accidents include: inexperienced motorcyclists, wide urban roads that incite speeding and risky overtaking maneuvers, flowing urban roads that encourage high speed and increased interaction between vehicles, and lack of infrastructure maintenance.Practical ApplicationsThe results obtained are a valuable asset to define measures that will be conveniently adapted to the group of accident on which we want to act. The methodology exposed in this paper is applicable to the study of road crashes that involve all types of actors, not only the motorcyclists, and in contexts different than those presented in Bogota.     

高速公路交通事故分析及预防对策研究

利用济青高速公路 1998～ 1999年发生的 10 85起交通事故数据 ,在资料收集、处理和统计分析的基础上 ,对影响高速公路交通事故的人、车辆、道路环境、天气和交通量等主要因素进行了分析 ,并与国外的统计结果进行对比研究 ,预测出随着高速公路交通量的增长 ,事故率将会增加。此外 ,笔者针对影响高速公路事故因素提出了主动性、被动性预防对策 ,这些对策的实施将会减少高速公路事故的发生     

Quantifying Vision Zero: Crash avoidance in rural and motorway accident scenarios by combination of ACC,AEB, and LKS projected to German accident occurrence

Abstract

Objective: The Vision Zero initiative pursues the goal of eliminating all traffic fatalities and severe injuries. Today’s advanced driver assistance systems (ADAS) are an important part of the strategy toward Vision Zero. In Germany in 2018 more than 26,000 people were killed or severely injured by traffic accidents on motorways and rural roads due to road accidents. Focusing on collision avoidance, a simulative evaluation can be the key to estimating the performance of state-of-the-art ADAS and identifying resulting potentials for system improvements and future systems.

This project deals with the effectiveness assessment of a combination of ADAS for longitudinal and lateral intervention based on German accident data. Considered systems are adaptive cruise control (ACC), autonomous emergency braking (AEB), and lane keeping support (LKS).

Methods: As an approach for benefit estimation of ADAS, the method of prospective effectiveness assessment is applied. Using the software rateEFFECT, a closed-loop simulation is performed on accident scenario data from the German In-Depth Accident Study (GIDAS) precrash matrix (PCM). To enable projection of results, the simulative assessment is amended with detailed single case studies of all treated cases without PCM data.

Results: Three categories among today’s accidents on German rural roads and motorways are reported in this study: Green, grey, and white spots.

Green spots identify accidents that can be avoided by state-of-the-art ADAS ACC, AEB, and LKS. Grey spots contain scenarios that require minor system modifications, such as reducing the activation speed or increasing the steering torque. Scenarios in the white category cannot be addressed by state-of-the-art ADAS. Thus, which situations demand future systems are shown. The proportions of green, grey, and white spots are determined related to the considered data set and projected to the entire GIDAS.

Conclusions: This article describes a systematic approach for assessing the effectiveness of ADAS using GIDAS PCM data to be able to project results to Germany. The closed-loop simulation run in rateEFFECT covers ACC, AEB, and LKS as well as relevant sensors for environment recognition and actuators for longitudinal and lateral vehicle control.

Identification of green spots evaluates safety benefits of state-of-the-art level 0–2 functions as a baseline for further system improvements to address grey spots. Knowing which accidents could be avoided by standard ADAS helps focus the evolution of future driving functions on white spots and thus aim for Vision Zero.     

Contributing factors of crash injury severity at public highway-railroad grade crossings in the U.S.

IntroductionThe Moving Ahead for Progress in the 21st Century (MAP-21) includes a separate program that supports safety improvements to reduce the number of fatalities and injuries at public highway-railroad grade crossings (HRGCs). This study identifies the significant factors affecting crash injury severity at public HRGCs in the United States.MethodCrashes from 2009 through 2013 on 5,528 public HRGCs, extracted from the Federal Railroad Administration database, were used in the analysis. A comprehensive list of risk factors was explored. Examples include predictors related to geographic region of crash, geometry (e.g., area type and pavement marking type), railroad (e.g., warning device type and railroad class), traffic (e.g., train speed and vehicles annual average daily traffic “AADT”), highway user (e.g., driver age and gender), and environment (e.g., lighting and weather conditions). The study used the mixed logit model to better capture the complex highway user behavior at HRGCs.ResultsFemale highway users were at higher risk of involvement in injuries and fatalities compared to males. Higher train speeds, very old drivers, open areas, concrete road surface types, and railroad equipment striking highway users before crash, were all found to increase the injury likelihood. On the other hand, young and middle-age drivers, non-passing of standing vehicles at HRGCs, industrial areas, and presence of warning bells were found to reduce injuries and fatalities.ConclusionsThe mixed logit model succeeded in identifying contributing factors of crash severity at public HRGCs and potential countermeasures to reduce both fatalities and injuries are suggested.Practical applicationsIt is important to install warning bells at public HRGCs, especially at those with high number of injury and fatality crashes. Enforcement of traffic nearby HRGCs is necessary to prevent vehicles from overtaking of standing vehicles.     

基于Logistic的不同车型碰撞行人事故严重程度致因分析

为定量分析不同车型碰撞行人事故严重程度影响因素,以美国北卡罗来纳州2007-2016年人车碰撞事故数据为样本,将其分为小轿车、SUV、货车碰撞行人事故3类,以事故严重程度为因变量,交通参与者属性、道路、环境条件和事故特征为候选自变量,分别建立累计logistic模型进行对比分析,探究人、车、路和环境因素对人车碰撞事故严...     

The impact of the economic crisis on occupational injuries

IntroductionThe potential influence of the current economic crisis on occupational accident rates and accident severity is studied in an analysis of all workplace accidents that occurred in Spain throughout the period 2000–2009.Method and resultsThe investigation confirms that occupational accidents in Spain are affected by the current economic crisis, which has provoked a sharp fall in both the number of accidents and the probability of having one. This may be justified by certain factors such as age, gender, length of service, size of the firm, and the employment stability of the injured worker. The influence of these factors is analyzed.Practical applicationsThe economic crises seems to provoke a sort of “natural selection” in the labor market and only the best adapted tend to remain (older workers, with more experience, a higher percentage of women, more workers in larger companies and permanent contracts), all of which means that the probability of workers having an injury is considerably reduced.     

The Driver Behaviour Questionnaire as accident predictor; A methodological re-meta-analysis

IntroductionThe Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include unpublished results.MethodThe present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken.ResultsOutlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, using the mean of accidents as proxy for effect indicated that studies where effects for violations are not reported have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r < .07) for violations versus traffic accident involvement, depending upon which tendencies are controlled for.ConclusionsMethodological factors and dissemination bias have inflated the published effect sizes of the DBQ. Strong evidence of various artefactual effects is apparent.Practical applicationsA greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.     

The effect of fatigue driving on injury severity considering the endogeneity

IntroductionFatigue driving is one of the most risky driving-related behaviors and represented a significant social and economic cost to the community. Several studies have already examined the relationship between fatigue driving behavior and traffic injury severity from different aspects. However, fatigue driving and injury severity in traffic crash may share some common influential factors. Ignoring the impact of these common factors will lead to endogeneity problem and result in biased parameter estimation.MethodBased on 38,564 crash records during 2006–2011 in Guangdong province, China, we apply a bivariate endogenous binary-ordered probit model to examine the relationship between fatigue driving and injury severity considering endogeneity of fatigue driving. We also explore the difference of influential factors between commercial and non-commercial vehicle drivers.ResultsThis study identifies several common observed influential factors of fatigue driving propensity and fatal injury propensity and reveals a substantial and significant negative correlation of unobserved factors between them.ConclusionsThe influence of fatigue driving on injury severity is significantly underestimated if the endogeneity of fatigue driving on fatal injury propensity is ignored. Factors such as vehicle insurance and road types not only affect fatal injury propensity, but also fatigue driving propensity.Practical applicationsThe findings in this study can help better understand how those factors affect fatigue driving and injury severity, and contributes to more efficient policy for preventing the harmfulness of fatigue-related crashes.     

An analysis of motorcycle injury and vehicle damage severity using ordered probit models

Problem: Motorcycles constitute about 19% of all motorized vehicles in Singapore and are generally overrepresented in traffic accidents, accounting for 40% of total fatalities. Method: In this paper, an ordered probit model is used to examine factors that affect the injury severity of motorcycle accidents and the severity of damage to the vehicle for those crashes. Nine years of motorcycle accident data were obtained for Singapore through police reports. These data included categorical assessments of the severity of accidents based on three levels. Damage severity to the vehicle was also assessed and categorized into four levels. Categorical data of this type are best analyzed using ordered probit models because they require no assumptions regarding the ordinality of the dependent variable, which in this case is the severity score. Various models are examined to determine what factors are related to increased injury and damage severity of motorcycle accidents. Results: Factors found to lead to increases in the probability of severe injuries include the motorcyclist having non-Singaporean nationality, increased engine capacity, headlight not turned on during daytime, collisions with pedestrians and stationary objects, driving during early morning hours, having a pillion passenger, and when the motorcyclist is determined to be at fault for the accident. Factors leading to increased probability of vehicle damage include some similar factors but also show some differences, such as less damage associated with pedestrian collisions and with female drivers. In addition, it was also found that both injury severity and vehicle damage severity levels are decreasing over time.     

The analysis of influence of individual and environmental factors on 2-wheeled users’ injuries

Objective: Powered 2-wheeled motor vehicles (PTWs) are one of the most vulnerable categories of road users. Bearing that fact in mind, we have researched the effects of individual and environmental factors on the severity and type of injuries of PTW users. The aim was to recognize the circumstances that cause these accidents and take some preventive actions that would improve the level of road safety for PTWs.

Methods: In the period from 2001 to 2010, an analysis of 139 road accidents involving PTWs was made by the Faculty of Transport and Traffic Engineering in Belgrade. The effects of both individual (age, gender, etc.) and environmental factors (place of an accident, time of day, etc.) on the cause of accidents and severity and type of injuries of PTWs are reported in this article. Analyses of these effects were conducted using logistic regression, chi-square tests, and Pearson's correlation.

Results: Factors such as categories of road users, pavement conditions, place of accident, age, and time of day have a statistically significant effect on PTW injuries, whereas other factors (gender, road type; that is, straight or curvy) do not. The article also defines the interdependence of the occurrence of particular injuries at certain speeds. The results show that if PTW users died of a head injury, these were usually concurrent with chest injuries, injuries to internal organs, and limb injuries.

Conclusions: It has been shown that there is a high degree of influence of individual factors on the occurrence of accidents involving 2-wheelers (PTWs/bicycles) but with no statistically significant relation. Establishing the existence of such conditionalities enables identifying and defining factors that have an impact on the occurrence of traffic accidents involving bicyclists or PTWs. Such a link between individual factors and the occurrence of accidents makes it possible for system managers to take appropriate actions aimed at certain categories of 2-wheelers in order to reduce casualties in a particular area. The analysis showed that most of the road factors do not have a statistically significant effect on either category of 2-wheeler. Namely, the logistic regression analysis showed that there is a statistically significant effect of the place of accident on the occurrence of accidents involving bicyclists.     

基于GIS的交通事故信息空间数据库研究

笔者分析了建立基于GIS的交通事故信息空间数据库的紧迫性;探讨了完备的交通事故信息数据库的内容构成,认为应包括空间数据库、影响因素数据库以及元数据和数据字典库三大部分;研讨了交通事故空间数据库的重要应用价值,进而采用GIS的分层组织思想对交通事故信息空间数据库中的数据进行组织;详细设计了各个数据表以及数据表间的关系,建立了包含交通事故对象、人、车、路以及环境等要素的交通事故空间数据库,为交通事故研究提供完备的数据支持。     

Analyzing injury severity of bus passengers with different movements

Objective: Though public transport vehicles are rarely involved in mass casualty accidents, when they are, the number of injuries and fatalities is usually high due to the high passenger capacity. Of the few studies that have been conducted on bus safety, the majority focused on vehicle safety features, road environmental factors, as well as driver characteristics. Nevertheless, few studies have attempted to investigate the underlying risk factors related to bus occupants. This article presents an investigation aimed at identifying the risk factors affecting injury severity of bus passengers with different movements.

Method: Three different passenger movement types including standing, seated, and boarding/alighting were analyzed individually using classification and regression tree (CART) method based on publicly available accident database of Great Britain.

Results: According to the results of exploratory analyses, passenger age and vehicle maneuver are associated with passenger injury severity in all 3 types of accidents. Moreover, the variable “skidding and overturning” is associated with injury severity of seated passengers and driver age is correlated with injury severity of standing and boarding/alighting passengers.

Conclusions: The CART method shows its ability to identify and easily explain the complicated patterns affecting passenger injury severity. Several countermeasures to reduce bus passenger injury severity are recommended.     

基于车辆事故等级分类的紧急呼救系统研究

基于交通事故紧急救援的现状,阐述建立车辆事故紧急呼救系统的新需求,提出了开发基于车辆事故严重等级分类的紧急呼救系统需要实现的功能;应用车辆碰撞安全性理论和研究成果、导航定位技术及通信技术,设计了基于事故严重等级分类的车辆事故紧急呼救决策流程;探讨车辆事故自动检测和等级分类及紧急救援的实施方案,以实现车辆事故紧急自动呼救,使车辆和伤员得到及时高效的紧急救助。