Abstract

The National Center for Statistics and Analysis and NHTSA suggest that head-on crashes are disproportionately represented in fatal crashes on two-lane highways, which constitute a substantial proportion of the highway network in the United States. This study focuses on analysis of the statistical association between head-on crash severity and potential causal factors, such as the geometric characteristics of the road segment, weather conditions, road surface conditions, and time of occurrence. Ordered probit models were estimated for data sets describing two-lane roads in Connecticut between 1996 and 2001. It was found that a wet roadway surface and narrow road segments were significantly related to more severe head-on crashes. A high density of access points and a nighttime occurrence of the crash were significantly related to more severe cases. Pavement width was found to be the most consistent factor, possibly because a wider road offers more space to avoid a direct head-on impact, thus reducing the severity of the crash. In addition, vehicle braking performance was important, as suggested by the higher probability of more severe head-on crashes on wet surfaces. The analysis results may be used by practitioners to understand the trade-off between geometric design decisions and head-on crash severity. Furthermore, identification of related factors will help to better explain crash phenomena and in turn to institute safer roadway design standards.

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