Analysis and Prediction of Vehicles Speed in Free-Flow Traffic

Abstract

Abstract Speed is a crucial factor in the frequency and severity of road accidents. Light and heavy vehicles speed in free-flow traffic at six locations on Poland’s national road network was analyzed. The results were used to formulate two models predicting the mean speed in free-flow traffic for both light and heavy vehicles. The first one is a multiple linear regression model, the second is based on an artificial neural network with a radial type of neuron function. A set of the following input parameters is used: average hourly traffic, the percentage of vehicles in free-flow traffic, geometric parameters of the road section (lane and hard shoulder width), type of day and time (hour). The ANN model was found to be more effective for predicting the mean free-flow speed of vehicles. Assuming a 5% acceptable error of indication, the ANN model predicted the mean free-flow speed correctly in 84% of cases for light and 89% for heavy vehicles.