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探讨道路特征对迎面相撞事故频率和严重程度的影响:来自马来西亚联邦道路的案例研究。

Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads.

机构信息

School of Civil Engineering, Universiti Sains Malaysia, USM Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia.

出版信息

Accid Anal Prev. 2014 Jan;62:209-22. doi: 10.1016/j.aap.2013.10.001. Epub 2013 Oct 11.

Abstract

Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes.

摘要

正面碰撞是最严重的碰撞类型之一,也是道路安全当局关注的重点。因此,有必要投入更多的努力来减少这种碰撞类型的发生频率和严重程度。为此,首先需要确定与碰撞发生相关的因素。这可以通过开发将碰撞结果与一组相关因素联系起来的碰撞预测模型来实现。本研究旨在确定影响马来西亚五条联邦道路 448 个路段正面碰撞发生频率和严重程度的因素。在 2007 年至 2010 年的 4 年期间,在研究路段上收集了有关道路特征和碰撞历史的数据。通过开发和比较包括泊松、标准负二项式 (NB)、随机效应负二项式、门限泊松、门限负二项式、零膨胀泊松和零膨胀负二项式在内的七种计数数据模型,拟合了正面碰撞的发生频率。为了对碰撞严重程度进行建模,考虑到已经发生了正面碰撞,使用了随机效应广义有序概率模型 (REGOPM)。就碰撞频率而言,根据拟合优度度量标准,发现随机效应负二项式 (RENB) 模型优于其他模型。根据模型的结果,发现水平曲率、地形类型、重型车辆交通和接入点等变量与正面碰撞的发生频率呈正相关,而限速和路肩宽度则降低了碰撞频率。关于碰撞严重程度,REGOPM 的结果表明,水平曲率、铺砌路肩宽度、地形类型和侧向摩擦力与更严重的碰撞有关,而土地利用、接入点和中央分隔带的存在降低了严重碰撞的可能性。基于本研究的结果,提出了一些潜在的对策,以最大限度地降低正面碰撞的风险。

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