title: Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads.
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.
authors.affiliation: School of Civil Engineering, Universiti Sains Malaysia, USM Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia.
authors.forename: Mehdi
authors.initials: M
authors.lastname: Hosseinpour
authors.forename: Ahmad Shukri
authors.initials: AS
authors.lastname: Yahaya
authors.forename: Ahmad Farhan
authors.initials: AF
authors.lastname: Sadullah
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000706:statistics & numerical data*; D004779:Environment Design / Q000706:statistics & numerical data*; D006801:Humans; D008296:Malaysia; D015233:Models, Statistical; D016012:Poisson Distribution; D012449:Safety; D015599:Trauma Severity Indices
keywords: Count-data models; Head-on crashes; Injury severity; Ordered probit model; Random effects