Abstract
There are a number of factors that cause motor vehicles to rollover. However, the impacts of roadway characteristics on rollover crashes have rarely been addressed in the literature. This study aims to apply a set of crash prediction models in order to estimate the number of rollovers as a function of road geometry, the environment, and traffic conditions. To this end, seven count-data models, including Poisson (PM), negative binomial (NB), heterogeneous negative binomial (HTNB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models, were developed and compared using crash data collected on 448 segments of Malaysian federal roads. The results showed that the HTNB was the best-fit model among the others to model the frequency of rollovers. The variables Light-Vehicle Traffic (LVT), horizontal curvature, access points, speed limit, and centreline median were positively associated with the crash frequency, while UnPaved Shoulder Width (UPSW) and Heavy-Vehicle Traffic (HVT) were found to have the opposite effect. The findings of this study suggest that rollovers could potentially be reduced by developing road safety countermeasures, such as access management of driveways, straightening sharp horizontal curves, widening shoulder width, better design of centreline medians, and posting lower speed limits and warning signs in areas with higher rollover tendency.
Highlights
Over 1.2 million people are killed in traffic crashes every year, and as many as 50 millions are injured
Note that original outcome of the logit model in the zero-inflated Poisson (ZIP) model is to estimate the probability of being in the zero rollover crash state
To compare the results of the logit model to those of the Poisson model estimating the crash frequency, we changed the sign of the coefficients so that the zero state of the ZIP model reflects the probability of being in the non-zero rollover group
Summary
Over 1.2 million people are killed in traffic crashes every year, and as many as 50 millions are injured. The global economic losses from road crashes are estimated to be more than US$ 500 billion annually (WHO 2009). In Malaysia, 414421 road crashes were reported in 2010, resulting in 6872 deaths and more than 9 billion ringgit of loss to the country’s economy (RMP 2011); of which, rollovers accounted for nearly 1.4% of the total fatal crashes (ITF 2012). According to the National Automotive Sampling System – Crashworthiness Data System (NASS–CDS), there are eight types of rollover crashes based on the cause and configuration of the collision _________. This article has been corrected since first published. Please see the statement of correct (DOI:10.3846/16484142.2016.1235833 of the erratum)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
