Abdulrahman Faden



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The Highway Safety Manual (HSM), which is the guidance document for state departments of transportation (DOTs), was published in 2010 and one of its sections, called Part C of HSM, it involves the development of crash prediction methods. The goal of the predictive method is to develop and calibrate safety performance functions (SPFs). SPFs are mostly regression models that correlate the expected number of crashes quantitatively with traffic exposure and geometric characteristics of the road. However, HSM's default prediction models are not suitable for all states or jurisdictions because each state and jurisdiction have different characteristics, such as terrain, driver behaviors, weather conditions, etc. Hence, the principal objective of this study is to develop a prediction method for producing Ohio-specific SPF models to use for rural two-lane highways in the state of Ohio. This study aims to create SPFs or jurisdiction-specific SPFs for two-lane rural highway segments as the first study for this type of roadway facility in the state of Ohio. Almost 28,700 miles of highway geometric data were obtained from the Highway Safety Information System (HSIS) to create these new models using negative binomial regression. The most critical variables to be used for analyzing and creating the best models for the state of Ohio are average annual daily traffic (AADT), segment length, lane width, shoulder width, posted speed limit, presence of curves and grades.

Publication Date


Project Designation

Graduate Research

Primary Advisor

Deogratias Eustace

Primary Advisor's Department

Civil and Environmental Engineering and Engineering Mechanics


Stander Symposium project, School of Engineering

United Nations Sustainable Development Goals

Sustainable Cities and Communities; Industry, Innovation, and Infrastructure

Development of Safety Performance Functions for Two-Lane Rural Highways in the State of Ohio