Analysis of factors affecting the severity of crashes in urban road intersections

The paper deals with the identification of factors affecting crash severity level at urban road intersections. Two official crash records together with a weather database, a traffic data source with data aggregated into 5 min intervals, and further information characterising the investigated urban intersections were used. Analyses were performed by using a back propagation neural network model and a generalized linear mixed model that enable the impact assessment of flow and other variables. Both methods demonstrate that flows play a role in the prediction of severity levels