LAUSR

Abstract The Fixing America's Surface Transportation Act (FAST Act) highlights a data-driven method to improve traffic safety on all public paved roads in the U.S. The first edition of the Highway Safety Manual (HSM) is a widely used tool that provides crash predictive models in the form of safety performance functions (SPFs). There are no specific SPFs for low-volume roadways in the HSM. It is important to know that low-volume roadways are the major roadway types in terms of total mileage. This study used 2015–2019 crash data from Texas, incorporating with other relevant geometric and traffic variables, to develop SPFs for a specific low-volume roadway type (rural minor collector roadways). This study proposed a rules-based SPF developed approach that makes the prediction accuracies higher compared to the full model. The R2 values range from 0.18 to 0.22 for all data (without splitting) for different injury level models. The prediction accuracies are improved in the decision tree-based models. For different class specific models (based on injury levels), the R2 values range from 0.25 to 0.41. Three SPF groups are developed based on crash injury types. The SPFs can provide guidance in refining the prediction accuracies of rural minor collectors.