Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: Case studies from Malaysian Federal Roads

被引:130
作者
Hosseinpour, Mehdi [1 ]
Yahaya, Ahmad Shukri [1 ]
Sadullah, Ahmad Farhan [1 ]
机构
[1] Univ Sains Malaysia, Sch Civil Engn, Nibong Tebal 14300, Penang, Malaysia
关键词
Head-on crashes; Count-data models; Injury severity; Ordered probit model; Random effects; MOTOR-VEHICLE CRASHES; ORDERED PROBIT MODELS; PROPORTIONAL ODDS MODELS; INJURY-SEVERITY; ACCIDENT FREQUENCIES; TRAFFIC CRASHES; RURAL INTERSECTIONS; PEDESTRIAN CRASHES; PREDICTION MODELS; REGRESSION-MODEL;
D O I
10.1016/j.aap.2013.10.001
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
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. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:209 / 222
页数:14
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