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611.
侧面碰撞乘员损伤影响因素分析 总被引:4,自引:0,他引:4
开发了侧面碰撞乘员胸部、腹部和髋部损伤影响因素分析模型,并经过多工况试验验证.在该模型的基础上研究了侧面碰撞侵入速度、侵入形态以及车门内饰系统刚度特性对乘员损伤的影响.得出结论是:控制侧面结构侵入速度在8m/s以下,在胸部撞击之前推开乘员的髋部(髋部提前)以及适当的车门内饰系统刚度特性,可以显著减轻对乘员的伤害. 相似文献
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614.
杨成和 《交通运输工程与信息学报》2008,6(1):20-25
本文对列车追踪间隔计算方法进行了探讨,分析影响列车追踪间隔因素,对缩短列车追踪间隔的途径进行了研究,提出了可采用较大的制动率、尽量紧凑布置咽喉区、采用较大号码的道岔、分级解锁等途径缩短列车追踪间隔。 相似文献
615.
基于驾驶适应性和人因工程的事故预防对策 总被引:1,自引:0,他引:1
统计分析表明,70%的交通事故与人有关,人是引发交通事故的主要原因。从驾驶员驾驶适应性和人因工程学角度阐述了引起交通事故的各要素如驾驶员的生理、心理因素,驾驶环境、道路条件、汽车设计、驾驶员管理等,并且从人、机环境方面探讨了交通事故的预防对策。分析表明,从驾驶员驾驶适应性和人因工程学角度分析影响驾驶员安全驾驶的内因与外因,对减少交通事故保障行车安全具有重要意义。 相似文献
616.
Zhigao ZHU Tiezhu LI Wenquan LI 《Journal of Transportation Systems Engineering and Information Technology》2008,8(2):80-84
With the growing of vehicles ownership, the vehicular exhaust emissions have become major sources of air pollution in cities. In this paper, the pollutants, carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbon (HC) are considered as evaluation factors. On the basis of the relation between the emission factors and vehicle's velocity and the relation amongst three parameters (Volume, Speed, and Density) of traffic flow, we have designed a model. This calculates the total quantity of pollutants emission from vehicles based on speed, proportion of vehicle types, and traffic volume. Using the theory of nonlinear programming, we have formed an optimal model in which the link capacity is one main constraint and the minimum of the total quantity of pollutants emission is the goal and designed its algorithm solution. The aim of our research is to find a method to control the quantity of traffic pollutants emission through adjusting and controlling the composition of vehicle types, and then the traffic volume and vehicle's running speed indirectly. Finally, the feasibility of the model is justified through a practical example. 相似文献
617.
针对“方位、距离法”测定目标运动要素存在的不足,提出运用最小二乘法原理,拟舍求取目标的相对运动要素,进而解算速度三角形,得到目标运动要素,以提高测定精度,减少绘图劳力。 相似文献
618.
出租车客运是城市公共交通的重要组成部分。根据对影响武汉市出租车市场的相关因素的分析,找出建立数学模型需要考察的变量,再结合各变量与出租车数量相关性的强弱,选取合适的模型变量,建立多元回归模型,并对建立的多元回归模型进行检验。 相似文献
619.
Ipek N. Sener Rachel B. Copperman Ram M. Pendyala Chandra R. Bhat 《Transportation》2008,35(5):673-696
This paper presents a detailed analysis of discretionary leisure activity engagement by children. Children’s leisure activity
engagement is of much interest to transportation professionals from an activity-based travel demand modeling perspective,
to child development professionals from a sociological perspective, and to health professionals from an active lifestyle perspective
that can help prevent obesity and other medical ailments from an early age. Using data from the 2002 Child Development Supplement
of the Panel Study of Income Dynamics, this paper presents a detailed analysis of children’s discretionary activity engagement
by day of week (weekend versus weekday), location (in-home versus out-of-home), type of activity (physically active versus
passive), and nature of activity (structured versus unstructured). A mixed multiple discrete-continuous extreme value model
formulation is adopted to account for the fact that children may participate in multiple activities and allocate positive
time duration to each of the activities chosen. It is found that children participate at the highest rate and for the longest
duration in passive unstructured leisure activities inside the home. Children in households with parents who are employed,
higher income, or higher education were found to participate in structured outdoor activities at higher rates. The child activity
modeling framework and methodology presented in this paper lends itself for incorporation into larger activity-based travel
model systems where it is imperative that children’s activity-travel patterns be explicitly modeled—both from a child health
and well-being policy perspective and from a travel forecasting perspective.
Ipek N. Sener is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. She received her M.S. degrees in Civil Engineering and in Architecture, and her B.S. degree in Civil Engineering from the Middle East Technical University in Ankara, Turkey. Rachel B. Copperman is currently a Ph.D. student at The University of Texas at Austin in transportation engineering. She received her M.S.E. from The University of Texas at Austin in Civil Engineering and her B.S. from the University of Virginia in Systems Engineering. Rachel grew up in Arlington, Virginia. Ram M. Pendyala is a Professor in Transportation at Arizona State University in Tempe. He teaches and conducts research in activity-based travel behavior modeling, multimodal transportation planning, and travel demand forecasting. He is the chair of the Transportation Research Board Committee on Traveler Behavior and Values and vice chair of the International Association for Travel Behaviour Research. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
Chandra R. Bhat (Corresponding author)Email: |
Ipek N. Sener is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. She received her M.S. degrees in Civil Engineering and in Architecture, and her B.S. degree in Civil Engineering from the Middle East Technical University in Ankara, Turkey. Rachel B. Copperman is currently a Ph.D. student at The University of Texas at Austin in transportation engineering. She received her M.S.E. from The University of Texas at Austin in Civil Engineering and her B.S. from the University of Virginia in Systems Engineering. Rachel grew up in Arlington, Virginia. Ram M. Pendyala is a Professor in Transportation at Arizona State University in Tempe. He teaches and conducts research in activity-based travel behavior modeling, multimodal transportation planning, and travel demand forecasting. He is the chair of the Transportation Research Board Committee on Traveler Behavior and Values and vice chair of the International Association for Travel Behaviour Research. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
620.
影响混合料SPT动态蠕变试验的因素很多,主要有混合料种类、试验温度、偏应力、围压等。本文分别对3种混合料Sup20、AC20S、和AC20S+聚酯纤维进行了不同条件下的试验,结果证明Sup20在推荐试验条件下抗变形能力最强;随着偏应力的增加,混合料Rs和实测Fn均减小;围压对高温高偏应力骨架嵌挤结构混合料的影响最大,可以相差10倍。所以,室内SPT动态蠕变试验所采用的围压不应该是定值,而应根据实际情况改变。 相似文献