Motorcycle crashes and fatalities have been increasing rapidly during thepast twelve years across the United States. In response to this issue, various studies have examined different aspects of motorcycle safety in recent years. However, there has been limited research on the effects of roadway geometry on motorcycle crashes, particularly at non-intersection locations. Typically, researchers employ Poisson and negative binomial crash prediction modeling techniques in these types of studies. The research presented in this paper uses a negative binomial model, applying Full Bayes methods to improve model performance, to assess the impacts of horizontal curvature and other geometric features on the frequency of single-vehicle motorcycle crashes along segments of rural two-lane roadways. The data used for this study includes crash records for the years 2002 through the spring of 2008, in combination with available geometric design information, for those curves maintained by the State of Ohio. The analysis data set includes 20,379 horizontal curves, which experienced a total of 225 motorcycle crashes during the study period. The findings show that the radius and length of each horizontal curve significantly influence the likelihood of motorcycle crashes, as do the location of the road segment relative to the curve, shoulder width, and average annual daily traffic.
Samenvatting