Traffic accidents represent an enormous cost to society in terms of property damage, productivity loss, injury and even death. According to the projections of the National Highway Traffic Safety Administration (NHTSA), 34,080 people in the U.S. died in crashes in 2012 (NHTSA, 2013a). This number represents an increase of 5.3% compared to 2011 and, as a result, 2012 is the first year with a year-to-year increase in fatalities since 2005. Additionally, roadway crashes are the leading cause of death in the U.S. among individuals 5-24 years of age (NVSR, 2012), and impose a tremendous emotional and economic burden on society. In this context, intersections are recognized as one of the most hazardous locations for severe injury crashes. Within the pool of intersection crashes, 30% occur at rural intersections and roughly a third of rural crashes involve fatalities (NHTSA, 2011) relative to 15% of urban intersection crashes that involve one or more fatalities. This disparity in fatality rates (given a crash) between rural and urban intersection crashes may be associated with several reasons, including driving situation in rural areas that motorists are less experienced with and slower emergency service response times in rural areas. In this study, we formulate and apply a novel approach for the joint modeling of crash frequency and crash type/injury severity at rural intersections in Central Texas that explicitly models the effects of variables on each of these dimensions, while also accommodating the joint nature of these two dimensions. In particular, we propose an integrated parametric framework for multivariate crash count data that is based on linking a univariate count model for the total count of crashes across all possible crash type/severity level states (i.e., crash event states) with a discrete choice model for crash event state given a crash. In this model, a variable that impacts the crash type or severity level of a crash also plays a role in the total count of crashes. The empirical results clearly reveal the benefits, both in terms of capturing flexibility in variable effects and data fit, to adopting the proposed structure. From a substantive standpoint, the results underscore the important effects of intersection design and major road characteristics in determining the number of crashes in each category. (Author/publisher)
Samenvatting