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单变量和两阶段方法估计严重程度碰撞频率的比较-双车道农村道路平曲线案例研究。

Comparison of univariate and two-stage approaches for estimating crash frequency by severity-Case study for horizontal curves on two-lane rural roads.

机构信息

Department of Civil Engineering, Ryerson University, 350 Victoria Street, Toronto, Canada.

Department of Civil Engineering, Central Tehran Branch, Islamic Azad University (IAUCTB), Emam Hasan Blvd., Ashrafi Esfahani Highway, District 2, Tehran, Iran.

出版信息

Accid Anal Prev. 2019 Aug;129:382-389. doi: 10.1016/j.aap.2018.08.015. Epub 2018 Sep 1.

Abstract

The Highway Safety Manual (HSM) procedures apply specific safety performance functions (SPFs) and crash modification factors (CMFs) appropriate for estimating the safety effects of design and operational changes to a roadway. Although the applicability of the SPFs and CMFs may significantly vary by crash severity, they are mainly based on total crash counts, with different approaches for estimation of crashes by crash severity. The variety of approaches in the HSM and in the literature in general suggests that there may be no one best approach for all situations, and that there is a need to develop and compare alternative approaches for each potential application. This paper addresses this need by demonstrating the development and comparison of alternative approaches using horizontal curves on two-lane roads as a case study. This site type was chosen because of the high propensity for severe crashes and the potential for exploring a wide range of variables that affect this propensity. To facilitate this investigation, a two-stage modeling approach is developed whereby the proportion of crashes for each severity level is estimated as a function of roadway-specific factors and traffic attributes and then applied to an estimate of total crashes from an SPF. Using Highway Safety Information System (HSIS) curve data for Washington state, a heterogeneous negative binomial (HTNB) regression model is estimated for total crash counts and then applied with severity distribution functions (SDFs) developed by a generalized ordered probit model (GOP). To evaluate the performance of this two-stage approach, a comparison is made with predictions directly obtained from estimated univariate SPFs for crash frequency by severity and also from a fixed proportion method that has been suggested in the HSM. The results revealed that, while the two-stage SDF approach and univariate approach adopt different procedures for model estimation, their prediction accuracies are similar, and both are superior to the fixed proportion method. In short, this study highlights the potential of the two-stage SDF approach in accounting for crash frequency variations by severity levels, at least for curved two-lane road sections, and especially for the all too frequent cases where samples are too small to estimate viable univariate crash severity models.

摘要

《公路安全手册》(HSM)程序适用于特定的安全性能函数(SPF)和碰撞修正因子(CMF),这些函数和因子可用于估算道路设计和运营变化对安全性的影响。尽管 SPF 和 CMF 的适用性可能因碰撞严重程度而有很大差异,但它们主要基于总碰撞次数,并且对于按碰撞严重程度估算碰撞的方法也有所不同。HSM 中的方法和一般文献中的方法多种多样,这表明对于所有情况可能没有一种最佳方法,因此需要为每种潜在应用开发和比较替代方法。本文通过将双车道道路上的水平曲线作为案例研究,展示了替代方法的开发和比较,从而满足了这一需求。选择这种类型的地点是因为严重碰撞的发生率很高,并且有可能探索影响这种倾向的广泛变量。为了便于进行这项调查,开发了一种两阶段建模方法,通过该方法,每个严重程度级别的碰撞比例被估计为道路特定因素和交通属性的函数,然后应用于 SPF 的总碰撞估计值。使用华盛顿州的公路安全信息系统(HSIS)曲线数据,对总碰撞次数进行了异质负二项式(HTNB)回归模型的估计,然后应用了广义有序概率模型(GOP)开发的严重程度分布函数(SDF)。为了评估这种两阶段方法的性能,将其与直接从按严重程度估算的单变量 SPF 获得的预测以及 HSM 中建议的固定比例方法进行了比较。结果表明,尽管两阶段 SDF 方法和单变量方法采用不同的模型估计程序,但它们的预测精度相似,并且都优于固定比例方法。总之,这项研究强调了两阶段 SDF 方法在解释严重程度的碰撞频率变化方面的潜力,至少对于曲线双车道路段如此,特别是对于样本太小而无法估计可行的单变量碰撞严重程度模型的情况更是如此。

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