This study examined the effects of various cross-section-related design elements on crash frequency and developed a crash prediction model for rural, multilane, non-freeway highways. According to the Poisson model that was developed, predicted crashes increase as a result of worsening roadside conditions, increasing exposure measures, increasing numbers of driveways per mile, and increasing intersections per mile. Predicted crashes decrease as a result of increasing outside shoulder widths and increasing median widths. The model also shows lower crash frequencies on multilane roads with partial access control compared to roads with no access control. This model can be used for a variety of applications, such as: (1) predicting crashes for different highway design alternatives; (2) estimating crash reductions attributed to changes in cross sections; and (3) assessing the potential safety impacts of upgrading a two-lane rural road to a multilane rural highway. A poisson regression model was used to model the relationship between expected accident frequency and various roadway and traffic variables.
The study results establish a quantitative relationship between accident frequency and various cross-section-related roadway design elements on rural, multi-lane, non-freeway highways.