Analysis And Modeling of Rural Roads Traffic Safety Data

Abstract

Traffic accidents threaten human’s safety and properties as well as restrict the management of transportation systems. Therefore, traffic accidents prediction models could help stakeholders to understand accident causes toward controlling their effects. This paper aims at developing a prediction model for a rural road in Egypt using actual accident data with survey data for pavement conditions, traffic flow presented as average hourly traffic per lane, speed, minor access, traffic signs conditions and road width. The relationship between accident number and the influencing factors is modeled using fuzzy logic algorithm which deals with nonlinear relationships between parameters. The results show that the developed model produced accurate and stable traffic accident predictions (R2=0.79). The results indicated that average accident rate decreases as road width increases where, a reduction in accident rate of about 5.26% is reached due to road width widening by 3.5m. The results indicate that road accidents on the studied road can be reduced by 7.38% if the speed is limited to 75 km/h. About 17.90% reduction is achieved by improving road surface condition. Also results indicate a positive relationship between traffic volume and accidents rate.