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Transfer of the Highway Safety Manual predictive method to German rural two-lane, two-way roads

机译:将公路安全手工预测方法转移到德国农村双车道,双向道路

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摘要

In Germany and Europe in general, a relevant proportion of all road fatalities occur in the nonmotorway rural road network. Although the predictive performance of most accident prediction models is unknown, theHighway Safety Manual(HSM) formulation offers a consistent method for making reliable crash frequency predictions. These considerations led to the development of a model to be used for making crash frequency on German rural two-lane, two-way road segments following theHSMapproach. The first step was the development of the base model by fitting a base safety performance function (SPF) to a group of 206 base sections, approximately 61 miles long. The full model was subsequently obtained by combining the base SPF with theHSMCrash Modification Factors (CMFs) and calibrating the model using the full data set (10,169 sections approximately 2,463 miles long). The goodness of fit (GOF) of the base and the full model was tested, showing a good fit for both. The GOF of the simple application of the originalHSMpredictive method was also tested, showing a very bad fit. This led to the conclusion that the research conducted constitutes a model that combines the consistency of theHSMapproach with a good fit to the German reality.
机译:在德国和欧洲一般来说,所有道路死亡的相关比例发生在非洲农村公路网。尽管大多数事故预测模型的预测性能是未知的,但高速公路的安全手册(HSM)配方提供了一种可靠的碰撞频率预测的一致方法。这些考虑因素导致开发用于在德国农村双车道上进行撞击频率的模型,双向双向道路段。第一步是通过将基本安全性能(SPF)拟合到一组206个基部,大约61英里长的基础模型的开发。随后通过将基础SPF与HSMCRASH修改因子(CMF)组合并使用完整数据集进行校准模型来获得完整模型,并使用全数据集(10,169个部分长约2,463英里)。测试底座和完整模型的适合度(GOF)的良好,表现出良好的两者都适合。还测试了原始高潮的简单应用的GOF,表现出非常糟糕的合身。这导致了所做的研究构成了一个模型,它结合了HeapRoach与德国现实良好的一致性。

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