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An Intellectualized Evaluation Model for Highway Safety Countermeasure of At-grade Intersection

机译:平面交叉口公路安全对策智能化评价模型

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In both at-grade intersections of highway and the area nearby, mixed traffic condition leads to severe traffic conflict, and causes traffic accident frequently happening. There are many factors with complicated inter-relationships that affect at-grade intersectionȁ9;s safety, and many uncertainties exist between traffic safety countermeasures and their expected effectiveness. In the process of developing and implementing countermeasures of highway traffic accident prevention, it is an essential task of current traffic safety management both to deal with the above-mentioned uncertainties effectively and to make scientific evaluation and selection of the countermeasures with an aim of allocating social resource reasonably. Upon a systematic analysis of both the characteristics of the traffic accidents and highway safety countermeasures in at-grade intersection, this paper proposes the at-grade intersection safety countermeasure system. With CRF (Crash Reduction Factor) borrowed from USA applied, the effectiveness analysis of highway safety countermeasures in at-grade intersection is implemented. Based on the above, and with help of Inductive Learning Approach, the intellectualized evaluation model (IEM) for highway safety countermeasure of at-grade intersection is established.
机译:在高速公路及其附近地区的两个平交路口,混合交通状况导致严重的交通冲突,并导致交通事故频繁发生。影响道路交叉口安全性的因素很多,相互关系复杂,交通安全对策与其预期效果之间存在许多不确定性。在制定和实施公路交通事故预防对策的过程中,有效地应对上述不确定性,科学地评估和选择对策,以期分配社会责任,是当前交通安全管理的一项基本任务。资源合理。在对路口交叉口交通事故特征及高速公路安全对策进行系统分析的基础上,提出了一种路口交叉口安全对策系统。运用美国借用的CRF(Crash Reduction Reduction Factor)技术,对平交路口的公路安全对策进行了有效性分析。在此基础上,借助归纳学习法,建立了平交路口高速公路安全对策的智能化评价模型(IEM)。

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