passenger vehicles

  • 文章类型: Journal Article
    目标:自动驾驶系统(ADS)车队目前正在美国的几个密集城市运营设计领域进行部署。在这些密集的城市地区,行人在历史上占了很大一部分,有时大多数人,伤害和致命的碰撞。对涉及行人和人工驾驶车辆的碰撞事件中的伤害风险的深入了解可以为持续的ADS开发和安全效益评估提供信息。目前没有对美国行人碰撞进行系统的调查,因此,这项研究使用德国深度事故研究(GIDAS)的重建数据来开发与车辆碰撞的行人的机械伤害风险模型。
    方法:研究在GIDAS数据库中查询了1999年至2021年涉及乘用车或重型车辆与行人碰撞的案例。
    方法:我们描述了乘用车对行人和重型车辆对行人碰撞的伤害模式和频率,重型车辆包括重型卡车和公共汽车。损伤风险函数是在AIS2+开发的,3+,涉及与乘用车正面碰撞的行人的4级和5级,以及与重型车辆正面碰撞的行人的4级和5级。模型预测因子包括碰撞速度的机械因素,行人年龄,性别,行人高度相对于车辆保险杠高度,和碰撞前的车辆加速。包括儿童(≤17岁)和老年人(≥65岁)行人。我们进一步进行了加权和估算分析,以了解缺失数据元素以及权重对德国行人撞车总数的影响。
    结果:我们确定了3,112名与乘用车发生碰撞的行人,其中2,524次碰撞是正面车辆撞击。此外,我们确定了154名与重型车辆相撞的行人,其中87起确认的碰撞是正面车辆撞击。与年轻人相比,儿童受到伤害的风险更高,严重伤害的风险最高(AIS3+)存在于数据集中最老的行人。与重型车辆的碰撞比与乘用车的碰撞更可能在低速下产生严重(AIS3)伤害。与乘用车和重型车辆的碰撞之间的伤害机制不同。最初的参与导致36%的行人在乘用车碰撞中受到最严重的伤害,与重型车辆碰撞的23%相比。相反,车辆底部在乘用车碰撞中造成了6%的最严重伤害,在重型车辆碰撞中造成了20%的伤害。
    结论:自2009年以来,美国行人死亡人数已上升了59%。我们必须了解和描述伤害风险,以便我们能够针对减少伤害和死亡的有效策略。这项研究建立在以前的分析基础上,包括最现代的车辆,包括儿童和老年行人,结合额外的机械预测因子,扩大包括在内的撞车事故的范围,并使用多重估算和加权来更好地估计相对于德国行人碰撞的整个人口的这些影响。这项研究是首次根据现场数据调查与重型车辆碰撞对行人造成伤害的风险。
    OBJECTIVE: Automated Driving System (ADS) fleets are currently being deployed in several dense-urban operational design domains within the United States. In these dense-urban areas, pedestrians have historically comprised a significant portion, and sometimes the majority, of injury and fatal collisions. An expanded understanding of the injury risk in collision events involving pedestrians and human-driven vehicles can inform continued ADS development and safety benefits evaluation. There is no current systematic investigation of United States pedestrian collisions, so this study used reconstruction data from the German In-Depth Accident Study (GIDAS) to develop mechanistic injury risk models for pedestrians involved in collisions with vehicles.
    METHODS: The study queried the GIDAS database for cases from 1999 to 2021 involving passenger vehicle or heavy vehicle collisions with pedestrians.
    METHODS: We describe the injury patterns and frequencies for passenger vehicle-to-pedestrian and heavy vehicle-to-pedestrian collisions, where heavy vehicles included heavy trucks and buses. Injury risk functions were developed at the AIS2+, 3+, 4+ and 5+ levels for pedestrians involved in frontal collisions with passenger vehicles and separately for frontal collisions with heavy vehicles. Model predictors included mechanistic factors of collision speed, pedestrian age, sex, pedestrian height relative to vehicle bumper height, and vehicle acceleration before impact. Children (≤17 y.o.) and elderly (≥65 y.o.) pedestrians were included. We further conducted weighted and imputed analyses to understand the effects of missing data elements and of weighting towards the overall population of German pedestrian crashes.
    RESULTS: We identified 3,112 pedestrians involved in collisions with passenger vehicles, where 2,524 of those collisions were frontal vehicle strikes. Furthermore, we determined 154 pedestrians involved in collisions with heavy vehicles, where 87 of those identified collisions were frontal vehicle strikes. Children were found to be at higher risk of injury compared to young adults, and the highest risk of serious injuries (AIS 3+) existed for the oldest pedestrians in the dataset. Collisions with heavy vehicles were more likely to produce serious (AIS 3+) injuries at low speeds than collisions with passenger vehicles. Injury mechanisms differed between collisions with passenger vehicles and with heavy vehicles. The initial engagement caused 36% of pedestrians\' most-severe injuries in passenger vehicle collisions, compared with 23% in heavy vehicles collisions. Conversely, the vehicle underside caused 6% of the most-severe injuries in passenger vehicle collisions and 20% in heavy vehicles collisions.
    CONCLUSIONS: U.S. pedestrian fatalities have risen 59% since their recent recorded low in 2009. It is imperative that we understand and describe injury risk so that we can target effective strategies for injury and fatality reduction. This study builds on previous analyses by including the most modern vehicles, including children and elderly pedestrians, incorporating additional mechanistic predictors, broadening the scope of included crashes, and using multiple imputation and weighting to better estimate these effects relative to the entire population of German pedestrian collisions. This study is the first to investigate the risk of injury to pedestrians in collisions with heavy vehicles based on field data.
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  • 文章类型: Journal Article
    Investigating biomechanics of injury patterns from motor vehicle collisions (MVCs) informs improvements in vehicle safety. This study aims to investigate two-vehicle MVCs involving a passenger car and specific injury patterns associated with sources of injury, collision biomechanics, vehicle properties, and patient outcomes.
    Retrospective cohort study conducted to evaluate the biomechanics of specific injury patterns seen in MVCs involving passenger cars using the Crash Injury Research Engineering Network database between the years 2005 and 2015.
    A total of 631 MVC cases were included from 2005 to 2015. The majority of cases involved injuries to the head or neck, the thorax, and the abdomen (80.5%). Head/neck injuries from the steering wheel were associated with significantly higher injury severity score compared to those from seatbelts (26.11 versus 18.28, P < 0.001) and airbags (26.11 versus 20.10, P = 0.006), as well as a >6-fold higher fatality rate (P = 0.019). Thoracic injuries caused by the center console were twice as likely to be fatal than those caused by the seatbelt (P = 0.09).
    Occupants suffering injuries to the head/neck, the thorax, and the abdomen had higher injury severity score and fatality rates compared to other body regions, demonstrating that manufacturing and safety guidelines should focus on minimizing these injury patterns. Head/neck injuries caused by the steering wheel were associated with worse outcomes compared to those caused by seatbelts and airbags, further emphasizing the benefits of these critical safety features. Integration of innovative safety features like center-mounted airbags may improve occupant safety.
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  • 文章类型: Journal Article
    在运输和道路安全研究中,了解车辆行驶的公里数作为暴露和机动性的指标至关重要。它以分类的方式在确定用户风险指数中的应用引起了科学界和负责确保高速公路道路安全的当局的极大兴趣。这项研究使用了在车辆技术检查站进行乘用车检查期间记录的数据样本,并将其存储在由西班牙交通总局管理的数据仓库中。本研究有三个显著特点:(1)探索了新的数据源,(2)所开发的方法适用于其他类型的车辆,根据数据允许的分解水平,(3)模式提取和流动性估计有助于道路安全指标的持续和必要改进,并与2030年议程联合国可持续发展目标的目标3(良好的健康和福祉:具体目标3.6)保持一致。从收到的样本创建了一个操作数据仓库,这有助于获得西班牙车队车辆行驶公里数的推断值,根据作者的知识,使用先进的统计模型无法到达。三种机器学习方法,CART,随机森林,和梯度增强,根据模型的性能指标进行了优化和比较。这三种方法确定了年龄,发动机尺寸,乘用车的皮重是对其出行方式影响最大的因素。
    Knowledge of the kilometers traveled by vehicles is essential in transport and road safety studies as an indicator of exposure and mobility. Its application in the determination of user risk indices in a disaggregated manner is of great interest to the scientific community and the authorities in charge of ensuring road safety on highways. This study used a sample of the data recorded during passenger vehicle inspections at Vehicle Technical Inspection stations and housed in a data warehouse managed by the General Directorate for Traffic of Spain. This study has three notable characteristics: (1) a novel data source is explored, (2) the methodology developed applies to other types of vehicles, with the level of disaggregation the data allows, and (3) pattern extraction and the estimate of mobility contribute to the continuous and necessary improvement of road safety indicators and are aligned with goal 3 (Good Health and Well-Being: Target 3.6) of The United Nations Sustainable Development Goals of the 2030 Agenda. An Operational Data Warehouse was created from the sample received, which helped in obtaining inference values for the kilometers traveled by Spanish fleet vehicles with a level of disaggregation that, to the knowledge of the authors, was unreachable with advanced statistical models. Three machine learning methods, CART, random forest, and gradient boosting, were optimized and compared based on the performance metrics of the models. The three methods identified the age, engine size, and tare weight of passenger vehicles as the factors with greatest influence on their travel patterns.
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  • 文章类型: Journal Article
    Objective: When 2 vehicles of different sizes collide, the occupants of the smaller vehicle are more likely to be injured than the occupants of the larger vehicle. The larger vehicle is both more protective of its own occupants and more aggressive toward occupants of the other vehicle. However, larger, heavier vehicles tend to be designed in ways that amplify their incompatibility with smaller, lighter vehicles (by having a higher ride height, for example). A 2012 study by the Insurance Institute for Highway Safety (IIHS) concluded that fatalities caused by design incompatibility have decreased in recent years. The current study was conducted to update the 2012 IIHS analysis and to explore trends in vehicle incompatibility over time. Methods: Analyses examined deaths in crashes involving 1- to 4-year-old passenger vehicles from 1989 to 2016 collected from the Fatality Analysis Reporting System (FARS). Trends in driver risk were examined by comparing driver death rates per million registered vehicle years across vehicle type and size. Trends in aggressivity were examined by comparing partner driver death rates across vehicle type and size. Results: Cars and SUVs have continued their trend toward reduced incompatibility. In 1989-1992, SUVs were 132% more likely to kill the driver in a partner car compared with when a car crashed with another car. By 2013-2016, this value had dropped to 28%. Pickups and cars remain just as incompatible in 2013-2016 as they were in 1989-1992, however (159% vs. 158%). Remaining pickup incompatibility may be largely due to excess curb weight rather than to shape or design features, because light pickups were just 23% more likely to kill the driver in a partner car compared with when a car crashed with another car. Conclusions: The trend toward reduced fleet incompatibility has continued in the latest crash data, particularly for cars and SUVs. Although pickup-car incompatibility has also decreased over time, pickups remain disproportionately aggressive toward other vehicles, possibly due to their greater average curb weight. Reducing the weight of some of the heaviest vehicles and making crash avoidance technology fitment more widespread may be promising means to reduce remaining fleet incompatibility. Identifying the source of remaining incompatibility will be important for safety improvements going forward.
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  • 文章类型: Journal Article
    In-depth studies on the recycling of typical automotive exterior plastic parts are significant and beneficial for environmental protection, energy conservation, and sustainable development of China. In the current study, several methods were used to analyze the recycling industry model for typical exterior parts of passenger vehicles in China. The strengths, weaknesses, opportunities, and challenges of the current recycling industry for typical exterior parts of passenger vehicles were analyzed comprehensively based on the SWOT method. The internal factor evaluation matrix and external factor evaluation matrix were used to evaluate the internal and external factors of the recycling industry. The recycling industry was found to respond well to all the factors and it was found to face good developing opportunities. Then, the cross-link strategies analysis for the typical exterior parts of the passenger car industry of China was conducted based on the SWOT analysis strategies and established SWOT matrix. Finally, based on the aforementioned research, the recycling industry model led by automobile manufacturers was promoted.
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