Crash risk factors associated with injury severity of teen drivers

This paper focuses on identifying crash risk factors associated with injury severity of teen drivers. Crash data obtained from the Highway Safety and Information System (HSIS) for the entire state of North Carolina, for years 2011 to 2013, was used for analysis and modeling. Among all the crashes during the study period, a total of 62,990 crashes involving teen drivers (15 to 19?years) were analyzed. A partial proportionality odds model was developed to identify factors contributing to injury severity of teen drivers. The results obtained indicate that teen drivers driving sports utility vehicles and pickup trucks are more likely to be severely injured when compared to teen drivers driving passenger cars. Teen drivers are more likely to be severely injured on weekdays, particularly during peak hours. The chances of teen drivers getting involved in severe injury crashes on Tuesdays and Fridays is higher when compared to Sundays. Age, gender, road configuration, terrain, adverse weather condition, and access control are observed to have a significant effect on teen driver's injury severity.     

汽车涂装质量的影响因素及控制策略研究

随着我国经济发展和科学技术水平的不断提高,汽车市场竞争日益激烈,汽车生产厂家着重提升汽车的整体性能,以此来争夺市场份额。同时,汽车整体性能的提升意味着车辆的环境适应能力的提高,在车辆行驶过程中,表面漆膜往往要耐受高温、湿热、寒冷的侵蚀,这对于汽车涂装质量而言是一个巨大的考验。并且,汽车涂装质量直接决定了人们选购时对车辆的第一印象,是汽车市场竞争力的重要影响因素。因此,文章将分析汽车涂装质量的几大影响因素,并提出相应的控制策略,以供相关从业人员参考。     

Odds of work zone crash occurrence and getting involved in advance warning,transition, and activity areas by injury severity

Work zone area types include advance warning area, transition area, and activity area. The geometric conditions, traffic control aspects, traffic operations, and driver's maneuverability differ within each work zone area type. Therefore, the odds of getting involved in a crash and factors associated with injury severity vary by work zone area type. The focus of this research is to examine the odds of getting involved in a crash in work zone advance warning, transition, and activity areas by injury severity. Five years (2010–2014) of crash data for the state of North Carolina was obtained from the Highway Safety Information Systems (HSIS) and used in this research. Three partial proportional odds models and one proportional odds model were developed using Statistical Analysis Software (SAS) in this research. The results indicate that the odds of getting involved in a work zone crash in the transition area when compared to the advance warning area is higher during cloudy weather condition, on wet roads and interstates, and on roads equipped with double yellow / no passing zone, with rigid post barrier, grass, and flexible post barrier median. Further, the odds of getting involved in a work zone crash in the activity area when compared to the advance warning area is higher during cloudy weather condition, on interstate and US routes, and on roads with stop and go signal, double yellow / no passing zone and flexible post barrier median. Overall, the findings indicate that the odds and factors associated with crash occurrence depend on the work zone area type. The odds of getting involved in a severe or moderate injury crash is higher on curved roads in all the three work zone area types compared to straight roads. It is higher 1) in the advance warning area on roads with semi-flexible post barrier medians, 2) in the transition area on US routes, and 3) in the activity area on dark lighted roads, US routes, and State routes. Overall, the odds of getting involved in a severe or moderate injury crash and associated factors vary by work zone area type. The findings from this research assist the practitioners to take precautionary measures and reduce the odds of getting involved in a crash by implementing work zone area-specific safety countermeasures.     

Modeling phone use prevalence and risk assessment among long-haul truck drivers in India

Research on distracted driving due to phone use has increased substantially over the past decades, however, very little is explored about commercial vehicle drivers (e.g., truck drivers) in this aspect. This study focused on examining the prevalence of phone use habits and the associated crash risk for data collected from 490 Indian truck drivers. The data on demographic details, driving history, phone use habits (in everyday life and during driving), history of receiving any penalty for phone use and incidences of crash occurrence, was collected through face-to-face interviews with the drivers. Binary logistic models were used to identify the factors affecting phone use habits during driving and the associated crash risk. Further, the incidences of receiving a penalty for the phone use were examined through cross-tabulation and chi-square statistics. The results showed that 55% of the drivers used a phone during driving, mainly for talking purpose. The model revealed that education, vehicle size, vehicle ownership and everyday life phone use habits were the significant factors associated with phone use while driving. Regarding the history of penalty receiving incidences, 41% of the drivers who used a phone during driving had received the penalty, and 52% of these penalty-receiving drivers were penalized repetitively. The model results for crash risk showed that the frequent phone users were 29 times more likely to be involved in a crash due to phone use compared to the non-frequent users. The results suggest a double level (legislative and company level) prohibition policy for phone use during driving for the truck drivers and also to enforce strict and effective legislative ban especially on the truck routes.     

Modeling injury severity of crashes involving trucks: Capturing and exploring risk factors associated with land use and demographic in addition to crash,driver, and on-network characteristics

Nearly 499,000 motor vehicle crashes involving trucks were reported across the United States in 2018, out of which 22% resulted in fatalities and injuries. Given the growing economy and demand for trucking in the future, it is crucial to identify the risk factors to understand where and why the likelihood of getting involved in a severe or moderate injury crash with a truck is higher. The focus of this research, therefore, is on developing a methodology, capturing and integrating data, exploring, and identifying risk factors associated with surrounding land use and demographic characteristics in addition to crash, driver, and on-network characteristics by modeling injury severity of crashes involving trucks. Crash data for Mecklenburg County in North Carolina from 2013 to 2017 was used to develop partial proportional odds model and identify risk factors influencing injury severity of crashes involving trucks. The findings indicate that dark lighting condition, inclement weather condition, the presence of double yellow or no-passing zone, road sections with speed limit >40 mph and curves, and driver fatigue, impairment, and inattention have a significant influence on injury severity of crashes involving trucks. These outcomes indicate the need for effective geometric design and improved visibility to reduce the injury severity of crashes involving trucks. The likelihood of a severe or moderate injury crash involving a truck is also high in areas with high employment, government, light commercial, and light industrial land uses. The findings can be used to identify potential risk areas, proactively plan and prioritize the allocation of resources to improve safety of transportation system users in these areas.     

基于Origin的隧道入口运行车速计算模型的探讨

运行车速被广泛的应用于检验公路线形。该文对运行车速计算模型采用了一个新的思路:考虑了隧道对运行车速的影响。该研究以人为本,分析了影响隧道入口驾驶员行车速度的三个主要因素:隧道洞内外光线差值、路基宽度差值以及洞口位置,运用Origin软件统计得出高速公路隧道入口运行车速计算模型。该研究完善了运行车速模型,为高速公路交通安全的评价提供了很好的前提条件。     

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.     

Factors affecting lane change crashes

This study aims to investigate the contributing factors affecting the occurrence of crashes while lane-changing maneuvers of drivers. Two different data sets were used from the same drivers' population. The first data set was collected from the traffic police crash reports and the second data set was collected through a questionnaire survey that was conducted among 429 drivers. Two different logistic regression models were developed by employing the two sets of the collected data. The results of the crash occurrence model showed that the drivers' factors (gender, nationality and years of experience in driving), location and surrounding condition factors (non-junction locations, light and road surface conditions) and roads feature (road type, number of lanes and speed limit value) are the significant variables that affected the occurrence of lane-change crashes. About 57.2% of the survey responders committed that different sources of distractions were the main reason for their sudden or unsafe lane change including 21.2% was due to mobile usage. The drivers' behavior model results showed that drivers who did sudden lane change are more likely to be involved in traffic crashes with 2.53 times than others. The drivers who look towards the side mirrors and who look out the windows before lane-change intention have less probability to be involved in crashes by 4.61 and 3.85 times than others, respectively. Another interesting finding is that drivers who reported that they received enough training about safe lane change maneuvering during issuing the driving licenses are less likely to be involved in crashes by 2.06 times than other drivers.     

Age and road safety performance: Focusing on elderly and young drivers

The existing literature on young and elderly drivers indicates that they have the highest crash risks compared to other age groups of drivers. This study improves our understanding of the risk factors contributing to young and elderly drivers' elevated crash risk by examining self-report data from the E-Survey of Road User's Safety Attitudes (ESRA). The primary objective of this study is to compare the attitudes and behaviours of young, elderly, and middle-age drivers in Canada, the United States, and Europe. The main focus is on the practice of driving while distracted by mobile phones and driving while fatigued, as these are two dangerous behaviours that demonstrate the impact age may have. The analyses consistently showed that there are differences in the responses attributable to age. In all regions, drivers aged 18–21 years consistently reported higher rates of distracted and fatigued driving and higher rates of perceived social and personal acceptability of these behaviours than drivers aged 35–54 years. Elderly drivers aged 65+ years reported even lower rates of these behaviours and acceptability. Young drivers were also the least likely to believe that distraction and fatigue are frequent causes of road crashes, while elderly drivers were the most likely to believe this. This pattern with respect to age repeats in the support for policy measures as well; young drivers are least likely to support zero tolerance policies for mobile phone use when driving, while elderly drivers are the most likely to support this measure. Multivariate logistic regression modeling confirmed that elderly drivers were the least likely to engage in the use of mobile phones while driving or driving while fatigued. Statistically significant results showed that the middle-age group was less likely than young drivers to read a text message/email or check social media while driving and driving while fatigued.     

Impact of driving style,behaviour and anger on crash involvement among Iranian intercity bus drivers

In developing countries such as Iran, due to the inadequate infrastructure for rail and air transportation facilities, intercity buses are the most common type of transportation for long distances. Because of the long hours of driving, bus driving is considered a challenging job. Moreover, given the high capacity of these vehicles, a small error from the driver could endanger many passengers' health. So, studying drivers' behaviours can be a key factor in decreasing the risk factors of crash involvement in these drivers. However, few studies have focused on intercity bus drivers' behaviours. This research uses a sample of 254 professional drivers that answered a self-report questionnaire on driving style (MDSI), driving behaviour (DBQ), and driving anger (DAS). A structural equation modelling (SEM) is used to investigate the psychometric properties of these questionnaires. The results show a positive correlation between maladaptive driving styles and driving behaviour, and a negative correlation between adaptive styles and driving behaviour. Significant differences are observed among drivers with and without crash history on their maladaptive driving styles and their driving anger scale. A binary logistic regression model is also developed to predict traffic crashes as a function of driving misbehaviour. The results suggest that factors related to driving anger are the main factors that increase the probability of misbehaviour and traffic crashes. The results also suggest that driving style and driving behaviour significantly predict crash risk among bus drivers. Aggressive driving is associated with an increased probability of crash involvement among intercity bus drivers. The findings can be used to inform the health promotion policies and provide regular interventions designed to improve driving safety among intercity bus drivers.     

城市快速路匝道合流区车辆交互行为模式

在城市快速路匝道合流区,驾驶任务难度主要来自于车辆与其周边车辆之间的动态交互,目前对这种交互行为的特征和机理的认识还不十分清楚。基于从无人机视频中提取的高精度车辆轨迹数据,提取出表征车辆交互行为的指标TTC和GAP,并结合速度、加速度、车道位置等其他指标,对车辆的交互过程加以刻画,从中获得了大量交互行为实例,并在此基础上归纳总结出9种典型的车辆交互行为模式。通过分析各模式特征发现：即使在相同的外部环境下,车辆交互行为模式也可能存在差异,这表明交互行为不仅与车辆之间的相对位置、时空距离、速度状态等环境因素有关,还与驾驶人的应对能力、动机及风险意识等认知心理有关;另外,不同的交互模式面临的风险不同,并且该风险既可能是周边车辆行为发生改变而被迫卷入,也可能是驾驶人自身主动寻求的结果;9种不同类型的交互行为模式,构成了驾驶人自行感知的4种风险状态互相转换的具体实现形式;在驾驶过程中,驾驶人努力寻找契机并选择某种交互行为模式在各个风险状态之间来回切换,并非仅由心理压力较大的危险态向压力较小的自由态转换,也会发生反向转换,前者主要由降低事故风险和减少认知努力的动机驱动,后者旨在追求行车效率,但同时驾驶人会付出更多的认知努力以对抗风险的增加,这充分反映了驾驶人试图在行车效率、事故风险与认知努力三方面取得平衡。研究成果对深化理解驾驶行为及其背后的决策机制具有积极意义。     

Factors associated with crashes due to overcorrection or oversteering of vehicles

The objective of this research is to identify factors associated with crashes due to overcorrection or oversteering of vehicles. Crash data was collected from 2011 to 2013 for the State of North Carolina in the United States. Logistic regression modeling was used to analyze crash data because of the dichotomous nature of the dependent variable (overcorrection or oversteering). The crash involvement due to overcorrection or oversteering of a vehicle decreased as the age of the driver increased. Drivers are 2.22 times more likely to overcorrect or oversteer when ill, 3.44 times more likely to overcorrect or oversteer when under fatigue, and 1.61 times more likely to overcorrect or oversteer when fallen asleep compared to normal physical conditions. Overall, driver characteristics and speed limit tend to play a major role in overcorrection or oversteering of vehicles. Programs to reduce impaired driving might help in the reduction of overcorrection or oversteering related crash fatalities or injuries. Additionally, training and driver education programs focusing on identified factors associated with crashes due to overcorrection or oversteering of vehicles will benefit drivers on how to respond during emergency or panic situations.     

机动车交汇时灯具炫目性的讨论

在背景亮度为1 cd/m2的晚上,摩托车及汽车驾驶员无论使用近光灯、转向信号灯或专用昼间行驶灯,在各交汇距离相对上升对比度阈值小于2时,均不会产生炫目,不会影响对向行驶摩托车驾驶员的观察和判断能力;而摩托车和汽车远光灯在任何距离时的相对上升对比度阈值远远大于2时,在摩托车和摩托车交汇时,会产生炫目,造成交通行驶隐患.     

自然驾驶状态下重型工程车驾驶人驾驶稳定性分析

重型工程车行驶过程中事故风险大,发生恶性事故的概率高,易造成重大生命和经济损失,其运输安全管理问题面临挑战.为探究重型工程车驾驶人驾驶稳定性与相关影响因素之间的关系,开展重型工程车自然驾驶试验,提取车辆运动学、道路条件、驾驶人状态和工作时间等数据;采用速度均值和速度标准差表征驾驶人驾驶稳定性,以睡眠模式、道路线形、道路...     

工况驾驶规范性及客观评价指标相关性的试验研究

通过引入驾驶评价指标和制动压力的控制及其要求规范了驾驶行为，为提高测试的准确性以及可重复性提供了保障。利用8名具有多年底盘测功机驾驶经验的驾驶员及两台轻型汽油车，在底盘测功机上开展了大量的新欧洲驾驶循环测试 （New European Driving Cycle，NEDC） 和全球轻型车统一循环测试 （Worldwide Harmonized Light Vehicles Test Cycle，WLTC），并以10 Hz为采样频率连续记录数据进行综合计算，得到驾驶评价指标结果。通过相关性分析，认定驾驶风格对油门扰动性的影响在 NEDC工况下比在 WLTC工况下的更大，主因是驾驶员在稳定工况下拥有更多的自由度。对于NEDC工况，可以通过设定IWR及EER限值来实现规范驾驶；对于WLTC工况，可以通过设定IWR和RMSSE限值来实现规范驾驶。此外，通过限制工况驾驶过程中的最大制动压力还为规范驾驶提供了有效途径。不仅为降低不同驾驶员对燃料消耗量测试的影响提供了参考，在我国汽车领域实现“双碳”目标的背景下，也为乘用车碳排放大数据采集的准确性提供了借鉴。     

Investigating fatal and injury crash patterns of teen drivers with unsupervised learning algorithms

Teenagers have been emphasized as a critical driver population class because of their overrepresentation in fatal and injury crashes. The conventional parametric approaches rest on few predefined assumptions, which might not always be valid considering the complicated nature of teen drivers' crash characteristics that are reflected by multidimensional crash datasets. Also, individual attributes may be more speculative when combined with other factors. This research employed joint correspondence analysis (JCA) and association rule mining (ARM) to investigate the fatal and injury crash patterns of at-fault teen drivers (aged 15 to 19 years) in Louisiana. The unsupervised learning algorithms can explore meaningful associations among crash categories without restricting the nature of variables. The analyses discover intriguing associations to understand the potential causes and effects of crashes. For example, alcohol impairment results in fatal crashes with passengers, daytimes severe collisions occur to unrestrained drivers who have exceeded the posted speed limits, and adverse weather conditions are associated with moderate injury crashes. The findings also reveal how the behavior patterns connected with teen driver crashes, such as distracted driving in the morning hours, alcohol intoxication or using cellphone in pickup trucks, and so on. The research results can lead to effectively targeted teen driver education programs to mitigate risky driving maneuvers. Also, prioritizing crash attributes of key interconnections can help to develop practical safety countermeasures. Strategy that covers multiple interventions could be more effective in curtailing teenagers' crash risk.     

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。      

Characteristic analysis for cognition of dangerous driving using automobile black boxes

Automobile black boxes are devices that collect information regarding vehicle operation and the driver’s operating situation in the case of a traffic accident. The information collected from the automobile black box, which can also be used during normal driving, can provide information about dangerous driving cognition. This study was designed to analyze characteristics of dangerous driving data and build a dangerous driving cognition system as follows. First, dangerous driving is divided into four types by considering the vehicle’s movement, such as acceleration, deceleration, turning and statistical data of traffic accidents. Second, dangerous driving data were collected by vehicle tests using the automobile black box, and characteristics of the driving data were analyzed to classify dangerous driving. Third, a standard threshold was chosen to recognize dangerous driving, and an algorithm of dangerous driving cognition was created. Finally, verification was conducted by vehicle tests with automobile black boxes embedded with the developed algorithm. The presented recognition methods of dangerous driving can be used for on/off-line management of drivers and vehicles. Scientific traffic accident databases can be built with this driving and accident information, and can be used in various industrial areas.     

Assessing the effect of inattention-related error and anger in driving on road accidents among Iranian heavy vehicle drivers

Extensive studies have examined the effect of variables such as demographic characteristics, insomnia, and working conditions of drivers individually on inattention-related error as well as expression of anger in driving. Nevertheless, so far no study has tested the concurrent effect of these factors on crashes. This study has dealt with indirect investigation of the effect of variables including demographic characteristics, insomnia, and working conditions of drivers on inattention-related error and expression of anger in driving (as mediation model). Next, the effect of these two variables on the probability of incidence of road crashes has been assessed among truck drivers. For this purpose, 780 Iranian truck drivers were interviewed by validated questionnaires including insomnia severity index (ISI), attention related driving errors scale (ARDES), and driving anger expression (DAX). To confirm the validity of these questionnaires, confirmatory factor analysis (CFA) was used. Next, structural equation modeling (SEM) was employed for investigating the relationships between these latent variables and truck drivers' demographic characteristics, working conditions and their crash involvement. SEM results indicated that as the severity of insomnia among drivers increased, they committed more inattention-related errors, and also expressed more anger during driving. Generally, the results of this study indicated that with increase in the extent of experience and safety knowledge of drivers and improvement in their working conditions and their sleep status, it is possible to reduce inattention-related error and expression of anger during driving among heavy vehicle drivers.     

汽车发动机机油欠压停车装置

汽车驾驶室都装设有机油欠压警告等信号装置，以提醒驾驶员警觉，但在实际营运过程中，驾驶员常常疏忽欠压警告信号，或为了完成运输定额，强行运行，结果造成车辆损伤。针对这种情况，城市公共汽车或其它车辆，应该在原有机油欠压信号指示装置的基础上，安装一种在机油欠压时，强制使发动机熄火的装置。