交通事故致因中的人为因素分析

为改善交通安全状况,减少交通事故,从最主要的因素——人为因素出发,分析其影响。导致事故发生的主要原因是:驾驶员处理交通事件的能力(包括新手、老年、酒精、药物、疲劳、压力等),驾驶员在驾驶时采取冒险行为(包括不正确使用安全带、超速、犯罪、自杀等)。结果表明:新手驾驶、饮酒驾驶、疲劳驾驶、不正确使用安全带驾驶等仍是影响交通安全的主要因素。     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

Association between driver and child passenger restraint: Analysis of community-based observational survey data from 2005 to 2019

Introduction: Crash data suggest an association between driver seatbelt use and child passenger restraint. However, community-based restraint use is largely unknown. We examined the association between driver seatbelt use and child restraint using data from a state-wide observational study. Methods: Data from Iowa Child Passenger Restraint Survey, a representative state-wide survey of adult seat belt use and child passenger safety, were analyzed. A total of 44,996 child passengers age 0–17 years were observed from 2005 to 2019. Information about driver seatbelt use and child restraint was directly observed by surveyors and driver age was reported. Logistic regression was used to examine the association between driver seatbelt use and child restraint adjusting for vehicle type, community size, child seating position, child passenger age, and year. Results: Over the 15-year study period, 4,114 (9.1%) drivers were unbelted, 3,692 (8.2%) children were completely unrestrained, and another 1,601 (3.6%) children were improperly restrained (analyzed as unrestrained). About half of unbelted drivers had their child passengers unrestrained (51.8%), while nearly all belted drivers had their child passengers properly restrained (92.3%). Compared with belted drivers, unbelted drivers had an 11-fold increased odds of driving an unrestrained child passenger (OR = 11.19, 95%CI = 10.36, 12.09). The association between driver seatbelt use and child restraint was much stronger among teenage drivers. Unbelted teenage drivers were 33-fold more likely (OR = 33.34, 95%CI = 21.11, 52.64) to have an unrestrained child passenger. Conclusion: These data suggest that efforts to increase driver seatbelt use may also have the added benefit of increasing child restraint use. Practical applications: Enforcement of child passenger laws and existing education programs for new drivers could be leveraged to increase awareness of the benefits of seatbelt use for both drivers themselves and their occupants. Interventions aimed at rural parents could emphasize the importance of child safety restraints.     

Multi-agent traffic simulations to estimate the impact of automated technologies on safety

Abstract

Objective: The objective of this article was to develop a multi-agent traffic simulation methodology to estimate the potential road safety improvements of automated vehicle technologies.

Methods: We developed a computer program that merges road infrastructure data with a large number of vehicles, drivers, and pedestrians. Human errors are induced by modeling inattention, aimless driving, insufficient safety confirmation, misjudgment, and inadequate operation. The program was applied to simulate traffic in a prescribed area in Tsukuba city. First, a 100% manual driving scenario was set to simulate traffic for a total preset vehicle travel distance. The crashes from this simulation were compared with real-world crash data from the prescribed area from 2012 to 2017. Thereafter, 4 additional scenarios of increasing levels of automation penetration (including combinations of automated emergency braking [AEB], lane departure warning [LDW], and SAE Level 4 functions) were implemented to estimate their impact on safety.

Results: Under manual driving, the system simulated a total of 859 crashes including single-car lane departure, car-to-car, and car-to-pedestrian crashes. These crashes tended to occur in locations similar to real-world crashes. The number of crashes predicted decreased to 156 cases with increasing level of automation. All of the technologies considered contributed to the decrease in crashes. Crash reductions attributable to AEB and LDW in the simulations were comparable to those reported in recent field studies. For the highest levels of automation, no assessment data were available and hence the results should be carefully treated. Further, in modeling automated functions, potentially negative aspects such as sensing failure or human overreliance were not incorporated.

Conclusions: We developed a multi-agent traffic simulation methodology to estimate the effect of different automated vehicle technologies on safety. The crash locations resulting from simulations of manual driving within a limited area in Japan were preliminary assessed by comparison with real-world crash data collected in the same area. Increasing penetration levels of AEB and LDW led to a large reduction in both the frequency and severity of rear-end crashes, followed by car-to-car head-on crashes and single-vehicle lane departure crashes. Preliminary estimations of the potential safety improvements that may be achieved with highly automated driving technologies were also obtained.     

A comparison of overtime patrol stops made inside and out of cluster identified hotspots

Objective: The annual rate of impaired driving crashes in the United States has remained nearly constant over the last decade. While engineers, educators, enforcement, and emergency response personnel have worked diligently in their combined efforts to reduce the loss of life, there is still significant progress to be made. One area of recent interest is the use of data driven enforcement. The basis for data driven enforcement is the use of statistical clustering to identify geographic areas that represent the location of problem identification for various criminal or traffic offenses. In the case of impaired driving fatalities, the clustering represents locations with high rates of impaired driving crashes. Law enforcement officers and supervisors may allocate resources towards more specifically and efficiently addressing problem areas.

Methods: While data driven enforcement has been proven to be an effective tool in addressing crime and traffic safety problems, it has been a slow process for agencies to adopt data driven techniques. This study aims to explore the difference in traffic stops made inside and outside of hotspot identified areas. The study uses data from the Stark County Operating a Vehicle Impaired Task Force between 2013 and 2014.

Results: The analysis determined that stop occurring in hotspot defined areas are more likely to result in impaired driving arrests and seatbelt citations. Additionally it is found that the average cost of impaired driving arrests is significantly cheaper for stops occurring inside of hotspot areas.

Conclusion: Clustering as a means of directing law enforcement efforts are a way to increase the productivity and benefits of law enforcement agencies with limited finances or personnel. From this study it is seen that traffic stops made within defined cluster or hot spot areas are more effective in resulting in OVI arrests.     

山区二级公路运营期常态交通风险评价

为客观准确地评价山区二级公路常态交通风险,将风险源分为动态风险源和静态风险源.首先,基于白化权函数的综合评价法建立事故后果模型,基于历史事故数据建立事故概率模型,以评价静态风险;其次,结合白化权函数和层次分析法(AHP)建立事故后果模型,采用有序Logit模型建立事故概率模型,以评价动态风险;最后综合动静态风险结果评价...     

道路交通环境中驾驶疲劳的生成模型研究

为预防由驾驶疲劳引起的交通事故,有必要研究在道路、交通和环境的综合影响下驾驶疲劳的生成机理。基于生理、心理学中的经典理论,借鉴国内外相关的研究成果,采用理论推理的方法对驾驶疲劳生成过程中驾驶员唤醒水平的变化规律及其影响因素进行分析。在此基础上建立了驾驶疲劳的生成模型,并将模型应用于工程实际。通过驾驶员唤醒水平的变化,指出驾驶疲劳的生成时刻,及其对驾驶时间的规定和道路、景观设计的影响。该模型以唤醒水平为核心,描述驾驶疲劳生成过程中驾驶员唤醒水平的变化规律,强调道路交通环境对驾驶员唤醒水平的影响。     

一种新的基于图模型的间歇过程故障监测方法

目前多元统计方法被广泛用于间歇过程故障监测并已经取得了比较好的效果。但是,统计模型的可解释性能比较差,很难直接利用操作人员积累的安全经验。为应对这些不足,提出了一种基于图模型的间歇过程故障监测方法。利用提出的定性建模方法,过程机理及操作人员的安全经验能够方便地表达。利用在线的过程变量数据和正向推理算法推断生产应处于的状态,利用安全知识及时地发现生产异常。当推断的结论与在线测得的结果矛盾或过程变量超过设定的安全限时,给出解释性输出。通过一个间歇反应案例,验证了提出的方法在模型的可解释性和利用安全经验方面的优势。     

The role of personality characteristics in young adult driving

BACKGROUND: Motor vehicle injury is the major cause of mortality among young adults. Information about the individual characteristics of those who drive dangerously could enhance traffic safety programs. The goal of this research was to examine the association between various personality-related characteristics and risky driving behaviors. METHODS: Young adults in Michigan, USA (n = 5,362) were surveyed by telephone regarding several personality factors (risk-taking, hostility, aggression, tolerance of deviance, achievement expectations) and driving behaviors (competitive driving, risk-taking driving, high-risk driving, aggressive driving, and drink/driving). Michigan driver records were obtained to examine offenses, serious offenses, driving offense points, crashes and serious crashes in the three pre-interview years. Multivariate regression analyses, adjusting for age, race, and marital status were conducted separately by sex to identify personality factors related to driving. RESULTS: For men and women, greater risk-taking propensity, physical/verbal hostility, aggression, and tolerance of deviance were significant predictors of a competitive attitude toward driving, risk-taking driving, high-risk driving, driving aggression, and drink/driving. Greater risk-taking propensity, physical/verbal hostility, aggression, and to a small degree, expectations for achievement predicted higher numbers of offenses, serious offenses, and points. CONCLUSION: Traffic safety policies and programs could be enhanced through recognition of the role personality factors play in driving behavior and the incorporation of this knowledge into the design and implementation of interventions that modify the behaviors associated with them.     

Motorists' knowledge,attitudes and practices toward alcohol-impaired driving/riding in Ghana

Objectives: The main objective of this study was to establish the knowledge, attitudes, and practices toward drink driving/riding as a risk factor for road traffic crashes in 3 regional capitals in Ghana.

Methods: The study used a face-to-face approach to randomly sample motorists who were accessing various services at fuel/gas stations, garages, and lorry terminals in 3 cities in Ghana.

Results: Over the previous 12 months, 24% of all motorists and 55% of motorists who were current alcohol users reported driving or riding a vehicle within an hour of alcohol intake. On average, motorists/riders who were current alcohol users consumed 4 standard drinks per drinking occasion. Generally, 83% of motorists who currently use alcohol walked, rode, or drove home after consuming alcohol away from their homes. Motorists/riders who reported drink driving were 4 times more likely to have had previous traffic violation arrests compared to those who reported no drink driving/riding (P =.001). Respondents were of the opinion that speeding was the major cause of traffic crashes, followed by driver carelessness, poor road conditions, inexperienced driving, and drink driving, in that order. Thirty-six percent of motorists who use alcohol had the perception that consuming between 6 and 15 standard drinks was the volume of alcohol that will take them to the legal blood alcohol concentration (BAC) limit of 0.08%. Compared to females, male motorists/riders were more likely to report drink driving (adjusted odds ratio [AOR] = 5.15; 95% confidence interval [CI], 2.31 to 11.47). Private motorists also reported a higher likelihood of drink driving compared to commercial drivers (AOR = 3.36; 95% CI, 1.88 to 6.02). Only 4% of motorists knew the legal BAC limit of Ghana and only 2% had ever been tested for drink driving/riding.

Conclusion: The volumes of alcohol that motorists typically consume per drinking occasion were very high and their estimates of the number of drinks required to reach the legal BAC limit was also very high. Provision of authoritative information advising motorists about safe, responsible, or low-risk levels of alcohol consumption is imperative. Many traffic violations including drink driving were reported, thus suggesting a need for enhanced policing and enforcement. However, given the low level of knowledge of the legal BAC limit, educating motorists about how many drinks will approximate the legal BAC should be intensified prior to an increase in enforcement; otherwise, the desired outcome of enforcement may not be achieved.     

Inclusion of phone use while driving data in predicting distraction-affected crashes

Introduction: Given the tremendous number of lives lost or injured, distracted driving is an important safety area to study. With the widespread use of cellphones, phone use while driving has become the most common distracted driving behavior. Although researchers have developed safety performance functions (SPFs) for various crash types, SPFs for distraction-affected crashes are rarely studied in the literature. One possible reason is the lack of critical distracted behavior information in the commonly used safety data (i.e., roadway inventory, traffic, and crash counts). Recently, the frequency of phone use while driving (referred to as phone use data) is recorded by mobile application companies and has become available to safety researchers. The primary objective of this study is to examine if phone use data can potentially predict distracted-affected crashes. Method: The authors first integrated phone use data with roadway inventory, traffic, and crash data in Texas. Then, the Random Forest (RF) algorithm was applied to assess the significance of the feature - phone use while driving - for predicting the number of distraction-affected crashes on a road segment. Further, this study developed two SPFs for distraction-affected crashes with and without the phone use data, separately. Both SPFs were assessed in terms of model fitting and prediction performances. Results: RF results rank the frequency of phone use as an important factor contributing to the number of distraction-affected crashes. Performance evaluations indicated that the inclusion of phone use data in the SPFs consistently improved both fitting and prediction abilities to predict distracted-affected crashes. Practical Applications: The phone use data provide new insights into the safety analyses of distraction-affected crashes, which cannot be achieved by only using the conventional roadway inventory and crash data. Therefore, safety researchers and practitioners are encouraged to incorporate the emerging data sources in reducing distraction-affected crashes.     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.     

高速公路交通安全现状分析及管理对策

为了分析高速公路交通安全现状,提出高速公路交通安全综合管理对策,采用对比分析法,研判当前高速公路交通安全形势,统计分析高速公路交通事故特征规律,提出基于“6E”的高速公路交通安全系统管理对策。以1994～2013年期间的高速公路交通事故统计数据为分析对象,采用事故起数、事故死亡人数、事故率、致死率、重大事故起数等作为评价指标,对比交通事故总量和不同等级公路事故情况,分析了当前我国高速公路交通安全形势。从交通安全执法管理的角度,对高速公路交通事故发生时间、事故形态、肇事车辆类型、事故原因、肇事驾驶人驾龄等进行了特征分析,在立法、教育、工程、执法、急救、评价6个方面,提出了高速公路交通安全管理系统化对策,为进一步认识当前高速公路交通安全形势,完善高速公路交通安全管理提供技术支持。     

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...     

The prevalence of seatbelt and mobile phone use among drivers in Riyadh,Saudi Arabia: An observational study

IntroductionRoad traffic injuries (RTIs) are the third leading cause of death in Saudi Arabia. Numerous factors may increase the likelihood of RTIs. The prevalence of risk factors associated with RTIs may vary due to several reasons. Because little is known about these risk factors locally, we examined the prevalence of mobile phone and seatbelt use and their association with spatial locations.MethodsThis is an observational study conducted at major highways and inner intersections throughout Riyadh, the country's capital. Two observers captured seatbelt and mobile phone use among drivers. Logistic regression models were constructed to examine the association between real estate prices and mobile phone or seatbelt use. Observations were categorized as taken place in an affluent neighborhood if the average price per square meter was above 2500 Saudi Riyal.ResultsA total of 1700 drivers were observed in 13 sites citywide. 13.8% of drivers were seen using mobile while driving and only a third of drivers (34%) were wearing seatbelts. Being at an affluent neighborhood was associated with close to three times higher odds of wearing seatbelts (OR = 2.7, 95% CI = 1.9–3.7) and also associated with 42% lower odds of mobile phone use among drivers (OR = 0.58, 95% CI = 0.36–0.92).DiscussionThis study found a high prevalence of traffic violations among drivers in Riyadh. Based on our estimate, 660,000 drivers are roaming the street during daytime while using their phones and they are less likely to wear seatbelts. Unfortunately, this estimate might contribute to increasing RTIs. Despite existing regulations, seatbelt use among drivers is significantly lower than in developed countries (i.e. USA 94%).ConclusionOur study found a high prevalence of traffic violations represented by lack of compliance with seatbelt and mobile phone use laws. These findings provide a basis for their underlying prevalence in SA. Practical applications: Public health prevention programs may use these findings to facilitate support to increasing investment in awareness campaigns and further enforcement by the traffic police to reduce RITs and improve population health.     

Modeling crash severity by considering risk indicators of driver and roadway: A Bayesian network approach

Introduction: Traffic crashes could result in severe outcomes such as injuries and deaths. Thus, understanding factors associated with crash severity is of practical importance. Few studies have deeply examined how prior violation and crash experience of drivers and roadways are associated with crash severity. Method: In this study, a set of risk indicators of road users and roadways were developed based on their prior violation and crash records (e.g., cumulative crash frequency of a roadway), in order to reflect certain aspect or degree of their driving risk. To explore the impacts of those indicators on crash severity and complex interactions among all contributing factors, a Bayesian network approach was developed, based on citywide crash data collected in Kunshan, China from 2016 to 2018. A variable selection procedure based on Information Value (IV) was developed to identify significant variables, and the Bayesian network was employed to explicitly explore statistical associations between crash severity and significant variables. Results: In terms of balanced accuracy and AUCs, the proposed approach performed reasonably well. Bayesian modeling results indicated that the prior crash/violation experiences of road users and roadways were very important risk indicators. For example, migrant workers tend to have high injury risk due to their dangerous violation behaviors, such as retrograding, red-light running, and right-of-way violation. Furthermore, results showed that certain variable combinations had enhanced impacts on severity outcome than single variables. For example, when a migrant worker and a non-motorized vehicle are involved in a crash happening on a local road with high cumulative violation frequency in the previous year, the probability for drivers suffering serious injury or fatality is much higher than that caused by any single factor. Practical applications: The proposed methodology and modeling results provide insights for developing effective countermeasures to reduce crash severity and improve traffic system safety performance.     

In-vehicle workload assessment: effects of traffic situations and cellular telephone use

PROBLEM: Assessment of drivers' on-road workload is an important traffic safety consideration. This study was conducted to examine the effects of cellular phone communication on driving performance, with particular emphasis on variations in task demand in different traffic situations. METHOD: Twelve participants were asked to drive on urban roads and motorways with or without concomitant mathematical-addition tests relayed via cellular phone. Measurements included task and driving performance, physiological responses, and compensatory behavior. RESULTS: Analysis of task performance revealed that mean response time was markedly increased (11.9%) for driving on urban roads compared to motorways. The mean driving speed only decreased 5.8% in the presence of phone tasks in comparison to normal driving without distractions. In addition, overall physiological workload increased through compensatory behavior in response to the phone tasks. CONCLUSIONS: Driving with phone use in different traffic environments induced measurable variations in driver workload. IMPACT ON INDUSTRY: When faced with heavy traffic, a greater safety margin is typically adopted, with more lowered driving speed and restricted phone use, and it can be assumed that there is a general trade-off between tasks to preserve driving safety.     

The effect of organizational justice as perceived by occupational drivers on traffic accidents: Mediating effects of job satisfaction

Introduction: Considerable research supports a positive association between the safety climate (which is a direct organizational factor) and safety performance (such as safe driving). However, indirect organizational variables that influence safe driving have gone largely unexplored. This study contributes to safety research by examining the relationship between organizational justice, which is a distal organizational factor, and traffic accidents and the mediating role of job satisfaction. Method: 233 occupational drivers employed by taxi and bus companies in South Korea participated in the study. Regression analysis was conducted using police records on participants' on-the-job traffic accidents. Results: The analysis shows that the mediation model is statistically significant. That is, drivers with a lower level of perceived organizational justice showed a higher frequency of traffic accidents, and the mediating effect of job satisfaction was also significant. Based on the results, implications and limitations are discussed. Practical applications: The findings demonstrate that in order to decrease traffic accidents, transportation companies would benefit by examining distal factors such as organizational justice. This approach suggests that the conventional framework for safety management should be broadened to include aspects of the entire organization.     

工程系统一体化安全风险模型研究

借鉴功能模拟原理,利用目标树-成功树-主逻辑图(GTST-MLD)框架,提出了一个一体化安全风险模型。该模型对关联于工程系统安全特性的目标、功能、结构、行为等因素予以综合,提供了从多层次研究解决安全问题的模型基础,克服了基于事件树/故障树模型的概率风险评估等传统方法而分别对系统结构、行为、事件进行研究的问题,支持实现在更高的系统功能层面上对系统安全性的分析研究。通过研究该模型在安全风险评估、事故因果关联分析、潜在交互作用鉴别中的应用,表明研究成果为解决复杂工程系统安全问题提供了新的分析手段。