Investigating driver injury severity patterns in rollover crashes using support vector machine models

Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector machine (SVM) models to investigate driver injury severity patterns in rollover crashes based on two-year crash data gathered in New Mexico. The impacts of various explanatory variables are examined in terms of crash and environmental information, vehicle features, and driver demographics and behavior characteristics. A classification and regression tree (CART) model is utilized to identify significant variables and SVM models with polynomial and Gaussian radius basis function (RBF) kernels are used for model performance evaluation. It is shown that the SVM models produce reasonable prediction performance and the polynomial kernel outperforms the Gaussian RBF kernel. Variable impact analysis reveals that factors including comfortable driving environment conditions, driver alcohol or drug involvement, seatbelt use, number of travel lanes, driver demographic features, maximum vehicle damages in crashes, crash time, and crash location are significantly associated with driver incapacitating injuries and fatalities. These findings provide insights for better understanding rollover crash causes and the impacts of various explanatory factors on driver injury severity patterns.     

Epidemiology of moderate-to-severe injury patterns observed in rollover crashes

BackgroundPrevious epidemiological studies have highlighted the high risk of injury to the head, thorax, and cervical spine in rollover crashes. However, such results provide limited information on whole-body injury distribution and multiple region injury patterns necessary for the improvement and prioritization of rollover-focused injury countermeasures.MethodsSampled cases representing approximately 133,000 U.S. adult occupants involved in rollover crashes (between 1995 and 2013) sustaining moderate-to-severe injuries were selected from the National Automotive Sampling System Crashworthiness Data System database. A retrospective cohort study, based on a survey of population-based data, was used to identify relevant whole body injury patterns.ResultsAmong belted occupants injured in rollover crashes, 79.2% sustained injuries to only one body region. The three most frequently injured (AIS2+) body regions were head (42.1%), upper extremity (28.0%), and thorax (27.1%). The most frequent multi-region injury pattern involved the head and upper extremity, but this pattern only accounted for 2.3% of all of occupants with moderate or worse injuries.ConclusionsThe results indicated that for rollover-dominated crashes, the frequently observed injury patterns involved isolated body regions. In contrast, multi-region injury patterns are more frequently observed in rollovers with significant planar impacts. Identification of region-specific injury patterns in pure rollover crashes is essential for clarifying injury mitigation targets and developing whole-body injury metrics specifically applicable to rollovers.     

装载量与罐式汽车侧倾稳定性关系的分析

在弯道或变道行驶时，由于非满载罐内液体货物的晃动，罐式汽车的侧倾稳定性将低于运输等量固体货物的汽车。本文分析了非满载罐内晃动液体质心位置的变化，通过建立罐式汽车侧翻数学模型，推导出了非满载罐式汽车稳态转向时的侧翻阈值计算公式，表明装载量对罐式汽车侧倾稳定性具有较大影响，并提出了改善罐式汽车侧倾稳定性的方法。     

负载相关的工程机械防倾翻系统研究

本文提出了针对部分工程机械的负载相关的防倾翻方法。该方法能实时地测得包含惯性力等因素在内的等效负载。文中讨论了等效负载的求取过程，并进行了模拟实验。     

液化天然气储罐翻滚事故分析

随着世界能源紧缺现状的出现,天然气工业在我国的不断发展,液化天然气成为了一种成效卓著的储运方式,那么,随乊而来的便是液化天然气的安全问题,分层、翻滚是液化天然气在储存过程中有可能出现的一种极其危险的事故现象。通过FLUENT模拟软件对LNG储罐中不同物性参数的液化天然气在罐体漏热情况下进行数值模拟,在此乊前通过计算对大型LNG储罐漏热进行求解,将计算得到的热流密度近似取成10W/m2,以此作为模拟时边界条件的罐壁、罐底漏热量,模拟得出翻滚发生的开始和结束时间,最后通过翻滚发生持续时间计算仅翻滚时所造成的LNG损失,约334 t,翻滚发生前,储罐内的气相空间压力梯度约为32 kPa/h,仅约20 min便会使储罐内正常操作压力超出安全阀设定压力。由此可见,液化天然气翻滚事故的发生不仅会造成液化天然气本身的一大浪费,同时也会对人身及财产安全构成巨大威胁,因此,深入研究LNG翻滚对社会发展具有深远意义。     

可翻转的回转工作台装置

为了解决现有的重型机床配套的常规回转工作台不具备翻转运动且定位精度低的问题,介绍一种可翻转的回转工作台装置.该装置除具备直线和回转两项运动功能外还具备翻转运动功能,具有回转定位精度高、进给箱的重量轻、翻转角度误差小的特点.     

Rollover crashes: predicting serious injury based on occupant, vehicle, and crash characteristics

The purpose of this research was to determine occupant, vehicle, and crash characteristics predicting serious injury during rollover crashes. We compared 27 case occupants with serious or greater severity injuries with 606 control occupants without injury or with only minor or moderate injury. Odds ratios (OR) for individual variables and logistic regression were used to identify predictive variables for serious injury associated with rollovers. Cases more often had thorax, spine, or head injury compared to controls that more often had extremity injuries. Intrusion (especially roof rail or B-pillar intrusion) at the occupant's position, the vehicle interior side and roof as sources of injury, and improper safety belt use were significantly associated with serious injury. Even when safety belt use or proper use was controlled for, occupants with greater magnitude of intrusion at their seat position were about 10 times more likely to receive serious injury. Although prevention of rollover crashes is the ultimate goal, it is important to develop safer vehicles and safety systems to better protect occupants who are involved in rollover crashes. This also requires improvement in data collection systems documenting these types of crashes.     

Thoracic injuries to contained and restrained occupants in single-vehicle pure rollover crashes

Around one in three contained and restrained seriously injured occupants in single-vehicle pure rollover crashes receive a serious injury to the thorax. With dynamic rollover test protocols currently under development, there is a need to understand the nature and cause of serious thoracic injuries incurred in rollover events. This will allow decisions to be made with regards to adoption of a suitable crash test dummy and appropriate thoracic injury criteria in such protocols. Valid rollover occupant protection test protocols will lead to vehicle improvements that will reduce the high trauma burden of vehicle rollover crashes. This paper presents an analysis of contained and restrained occupants involved in single-vehicle pure rollover crashes that occurred in the United States between 2000 and 2009 (inclusive). Serious thoracic injury typology and causality are determined. A logistic regression model is developed to determine associations between the incidence of serious thoracic injury and the human, vehicle and environmental characteristics of the crashes. Recommendations are made with regards to the appropriate assessment of potential thoracic injury in dynamic rollover occupant protection crash test protocols.     

Heterogeneous impacts of gender-interpreted contributing factors on driver injury severities in single-vehicle rollover crashes

In this study, a mixed logit model is developed to identify the heterogeneous impacts of gender-interpreted contributing factors on driver injury severities in single-vehicle rollover crashes. The random parameter of the variables in the mixed logit model, the heterogeneous mean, is elaborated by driver gender-based linear regression models. The model is estimated using crash data in New Mexico from 2010 to 2012. The percentage changes of factors’ predicted probabilities are calculated in order to better understand the model specifications. Female drivers are found more likely to experience severe or fatal injuries in rollover crashes than male drivers. However, the probability of male drivers being severely injured is higher than female drivers when the road surface is unpaved. Two other factors with fixed parameters are also found to significantly increase driver injury severities, including Wet and Alcohol Influenced. This study provides a better understanding of contributing factors influencing driver injury severities in rollover crashes as well as their heterogeneous impacts in terms of driver gender. Those results are also helpful to develop appropriate countermeasures and policies to reduce driver injury severities in single-vehicle rollover crashes.     

汽车静态最大侧倾稳定角及其影响因素敏感度分析

为更加准确地求解汽车静态最大侧倾稳定角，建立了综合考虑悬架组合角刚度和轮胎垂直刚度的汽车静态侧翻模型。应用该模型，对某型号客车的静态最大侧倾稳定角进行了计算，将求解结果和其他侧翻模型以及试验数据对比，结果表明该模型计算结果和试验数据很接近。利用该模型，还进行了侧倾稳定角主要影响因素的敏感度分析。