2016
DOI: 10.3846/16484142.2016.1193046
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Evaluating the Effects of Road Geometry, Environment, and Traffic Volume on Rollover Crashes

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), z… Show more

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Cited by 23 publications
(22 citation statements)
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References 46 publications
(61 reference statements)
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“…These results indicate that the presence of over-dispersion in the short-term crash data is due to both excess zeroes and unobserved heterogeneity. Without considering the random effect, most of the research [29,30,31,32] about crash frequency modeling using hurdle models found that hurdle negative binomial models are not convergent or not preferred. For example, Hosseinpour et al [30] have found that the hurdle Poisson model instead of the hurdle negative binomial model was the best one among different models being considered in terms of comparative measures.…”
Section: Methodsmentioning
confidence: 99%
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“…These results indicate that the presence of over-dispersion in the short-term crash data is due to both excess zeroes and unobserved heterogeneity. Without considering the random effect, most of the research [29,30,31,32] about crash frequency modeling using hurdle models found that hurdle negative binomial models are not convergent or not preferred. For example, Hosseinpour et al [30] have found that the hurdle Poisson model instead of the hurdle negative binomial model was the best one among different models being considered in terms of comparative measures.…”
Section: Methodsmentioning
confidence: 99%
“…As an alternative to zero-inflated models, hurdle models have some inherent advantages on model assumptions. By relaxing the structural zero assumption, hurdle models assume that all zeroes in the crash data are sampling zeroes [29,30,31,32]. In contrast to the structural zero assumption presuming an inherently safe condition with no crashes, sampling zero assumption implies that all segments have crash potential and the zero state does not remain permanently on any road segment [29,30,31,32].…”
Section: Introductionmentioning
confidence: 99%
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“…The most dangerous branch of transport is land transportation, including road and rail traffic [13]. It is this area of transportation where inter-vehicle collisions or collisions with fixed obstacles are the most frequent.…”
Section: Environmental Hazards Resulting From Transport Collisionsmentioning
confidence: 99%