Comparative assessment of the accuracy of accident forecasting on the urban passenger transportation network

The paper presents a comparison of four methods of accident prediction, namely: fuzzy logic, neural networks, adaptive neuro-fuzzy inference and autoregressive moving average. The comparison is made on the basis of accident rate data on the street-road network operated in urban passenger transportation. The comparison results are shown and ways of further improvement of the evaluated methods are determined.