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汽车后视镜撞击试验台的研制 总被引:1,自引:0,他引:1
为使汽车后视镜撞击试验规范化,按照GB15084—1994标准的要求及方法专门研制了汽车后视镜撞击试验台,简扼地介绍了这一试验设备的结构及使用方法,用它可以完成各种汽车内后视镜和外后视镜的撞击试验,从而实现标准中规定的试验要求。 相似文献
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A. Esnaola I. Ulacia B. Elguezabal E. Del Pozo De Dios J. J. Alba I. Gallego 《International Journal of Automotive Technology》2016,17(6):1013-1022
The development and validation of a modular composite impact structure is presented in the present paper. Quasi-static and dynamic impact tests of the composite components and a full frontal crash test of a vehicle prototype with composite impact structures manufactured by a new UV-pultrusion process have been performed. The results have demonstrated the feasibility of composite impact structures for crash applications with high specific energy absorption values compared with current metallic crash structures. Furthermore, due to the high production capacity of this new manufacturing process, cost-effective composite impact structures for mass-production of conventional cars may be feasible. Finally, a multimaterial numerical model as design tool for crashworthiness applications has also been validated. Different accelerations measured in the crash test have been accurately predicted as well as the crash behaviour of the composite impact structures. 相似文献
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为了掌握假人大腿伤害机理,解决汽车实际碰撞中假人大腿伤害超标问题,文章首先通过应用Hyperworks和Dyna等软件仿真分析得出大腿伤害的机理,即碰撞中假人下肢与仪表板第1个接触点是假人的小腿且会造成较大的膝盖滑移量,然后针对具体车型问题提出降低仪表板刚度的优化方案,最终通过实车碰撞试验验证解决方案的有效性。提出保证碰撞中假人下肢与仪表板的第1个接触点是假人膝盖的IP型面的设计方案。 相似文献
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针对现有研究多基于病例对照的欠采样方法,即每起事故从连续交通流数据中按一定比例抽取对照的非事故数据构建模型,而该类模型在连续数据环境中的预测精度存在缺陷的状况,对城市交通连续观测并动态调控的技术环境(简称连续数据环境)开展道路交通事故风险预测模型构建研究。首先提出基于全样本交通流数据,结合“调整事故分类阈值”的方法解决事故风险预测研究中的非平衡数据分类问题;而后采用上海市城市快速路2014年5,6月的线圈检测交通流数据及历史事故数据开展实证研究,以受试者工作特征曲线下面积为评价指标,对比基于全样本和抽样样本构建的常用事故风险预测模型(逻辑回归、随机森林)的整体预测能力;以灵敏度和特异度的几何均数为评价指标,对比3种分类阈值计算方式(约登指数法、事故占比法和交叉点法)对事故/非事故综合预测精度的影响。结果表明:在连续数据环境下,采用全样本数据建模能使模型整体预测能力提高13.06%;基于约登指数法进行分类阈值计算可使模型的事故/非事故综合预测精度最佳。 相似文献
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Evaluation of safety benefits of automatic crash information notification systems on freeways 总被引:1,自引:0,他引:1
The automatic crash information notification system (ACINS) is an effective technology to enhance the potential for saving crash victims by reducing the crash response time (CRT) of emergency medical services. Shorter CRT results in a greater potential to save the lives and to alleviate the severity of injuries for crash victims. To fully operate the ACINS, reliable assessments of the safety benefits would be needed for justifying public investment. This study proposed a methodology for quantifying the effectiveness of the ACINS and applied the methodology to the Korean freeway system. The proposed methodology consists of three steps. The first step is to develop a statistical model for predicting injury severity of crash victims using ordered logistic regression. The second step is to estimate the amount of reduced CRT by applying ACINS. The effectiveness of the ACINS, which are defined as the number of reduced fatalities and severe injuries, were evaluated with the consideration of the market penetration rate (MPR) in third step. It has been found that approximately 9.4–15.4% of fatalities can be reduced with 100% MPR when the proposed methodology is applied to 2011 freeway crash data. The outcomes of this study support decision making for public investments and for establishing relevant traffic safety policies. 相似文献
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中国汽车工程研究院与中国保险行业协会联合发布"中国保险汽车安全指数测评规程",其中小偏置碰撞尤为引人关注,如何提高车辆小偏置碰撞工况的等级评定降低保费是主机厂当前的首要任务。通过对小偏置碰撞工况的评分原则进行详细介绍和解析,并以试验结果为依据,研究得出车体结构对小偏置碰撞整体等级评定起决定作用,驾驶员在此工况下下肢受伤残风险最高。为研究应对小偏置碰撞的车体结构,以某款SUV车型仿真结果为基础,详细介绍小偏置碰撞工况下车体变形特点,同时结合理论分析,提出三类优化方案,并对其进行优缺点说明,这三类优化方案为车身设计提供导向作用。针对该车型选择第二类优化方案,车体结构等级评定由"较差"提升为"优秀"。 相似文献
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《国际交通安全学会研究报告》2021,45(4):561-573
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. 相似文献