DEVELOPMENT OF AN ACCIDENT PREDICTOR INTERFACE FOR PREDICTING ACCIDENT POTENTIALS OF TRANSPORT VEHICLES IN NIGERIA

In this work, an accident prediction model was developed for determining the accident potential of a vehicle while on transit. The developed model identifies Human factors (HF), Mechanical factors (MF) and Environmental factors (EF) as the main factors responsible for vehicle crashes. The accident data used for this research was obtained from the Nigerian Federal Road Safety Corps (FRSC). Analysis of the accident data showed that HF contributes 0.846 accident probability, MF contributes 0.138 accident probability while EF contributes 0.016 accident probability. Also, driver’s age, distance of travel and maintenance frequency of the vehicle were considered in the development of the model, since they also play significant roles in determining accident probabilities. The model gives results ranging from 0-1. When the value is close to 0, it signifies low accident probability while values close to 1 signify high accident probability. An accident predictor interface was developed by combining all the possible accident cause factors. The accident predictor interface gave the least accident probability value of 0.2892 for the following combination: driver age of 60+ years, regular maintenance frequency and travel distance of C ≤ 250 Km. Application of the results of this model will significantly reduce the rate of road accident occurrences. Finally, transport companies and fleet owners are encouraged to embrace and use this innovation for safer operations.