Prediction of Road Accident Risk for Vehicle Fleet Based on Statistically Processed Tire Wear Model

The goal of the paper is to investigate impact tire tread depth on road accident risk and develop an rate prediction model. state 4288 vehicle tires using gauge was inspected processed statistically. most worn from each registered for further analy-sis. Based collected data, a statistical model insurance company fleet had been developed. conformity gamma distribu-tion data verified upon applying Pearson compatibility criterion. provides histo-grams frequencies depths theoretical curves distribution density. prob-ability depending (adaptive index) calculated formed distributions index dependence fleet. Accord-ing developed model, upgrade regulation minimum allowed by 2 mm (up 3.6 mm) could reduce (caused poor adhesion surface) 19.3% chosen Such models are useful safety experts, companies cost evaluation specialists predicting expenses related events.