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事故易发路段的判别是安全管理的重要内容之一。传统的事故易发路段判别方法多应用于运营阶段的公路,其判别精度很大程度决定于历史事故记录的周期和质量,且受“回归到平均”等现象的影响。对于实际的安全管理工作,预先对某一对象成为事故易发路段的可能性进行预测,进而预先采取安全改进措施,能够使得安全完善工作由被动变主动,还可增加事故易发路段判别工作的应用阶段。通过对大量双车道公路事故易发路段样本的整理和分析,发现接入口密度、道路线形、交通组成等要素对事故易发路段的产生有很大影响。为此,借助Log istic模型在概率预测上的优势对上述要素对事故易发路段形成的影响情况进行了研究,建立了事故易发路段预测模型,并进行了实际检验。
Discrimination of the accident prone section is one of the important contents of safety management. The traditional method of distinguishing easily accidental road segments is mostly applied to the highway in operation stage. The accuracy of the decision is largely determined by the cycle and quality of historical accident records and is affected by such phenomena as “return to average” and so on. For the actual safety management work, it is predicted in advance that the probability of an object becoming an accident prone road section, and then the safety improvement measures taken in advance, so that the safety improvement work can be changed from passive to active, and the identification of the accident prone section can be increased Application stage. Through the collation and analysis of a large number of samples of two-lane highway accident prone road sections, it is found that the factors such as access density, road alignment and traffic composition have a great impact on the occurrence of road sections prone to accidents. Therefore, the influence of the above factors on the formation of accident prone road sections is studied based on the advantage of Log istic model in probability prediction. The prediction model of accident prone sections is established and the actual test is carried out.