Development of Road Accident Prediction Models for Akure-Owo Highway, Ondo State, Nigeria

The aim of this study is to develop road accident prediction models for Akure- Owo highway. These relate accident numbers (as a dependent variable) with possible causes of accidents that are related to road factors (as independent variables). The study also proposes effective countermeasures to reduce the frequency and severity of traffic accidents in Nigeria. This research developed a Mathematical Accident Prediction Model using Spot Speed of Vehicles, Condition of Shoulder, Pavement Condition, Width of Pavement, Gradient of Pavement, Intersection, Drainage Condition, Stopping Sight Distance, and Overtaking Sight Distance as parameters from which the acronym SCPWGIDSO was formed. Accident data for six years (2010 to 2015) were obtained from Federal Road Safety Commission (FRSC) Akure office, which were used to identify accident prone locations along Akure-Owo highway. Twenty-four locations called “Black Spots” were identified. Field data such as Spot Speed of Vehicles, Condition of Shoulder, Pavement Condition, Width of Pavement, Gradient of Pavement, Intersection, Drainage Condition, Stopping Sight Distance, and Overtaking Sight Distance information were obtained from road condition survey. The SCPWGIDSO-AV rating system and weights produced a calibrated mathematical model, which was validated with field data.