Motorcycle crashes and fatalities have been increasing rapidly during the past 12 years both in Ohio and across the rest of the United States. In response to these issues, various studies have examined aspects of motorcycle safety in recent years. However, there has been limited research on the effects of site-specific roadway geometry on the frequency of motorcycle crashes, particularly at nonintersection 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 and 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 highways. The data used in this study include 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 30,379 horizontal curves that 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 frequency of motorcycle crashes, as do shoulder width, annual average daily traffic, and the location of the road segment in relation to the curve.
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