Geo-referenced data and complex networks for measuring road accident risk

The assessment of risk related to car crashes in road networks is a relevant topic for both social impact and the related political/administrative decisions. To this end, we show how the spatial objects and the information concerning the structure of the roads along with the crash history can be used to map the risk related to any road of a network. In particular, we follow a combined approach. On the one hand, a statistical model is developed in order to assess the risk on the basis of a set of features related to the characteristics of the streets. On the other hand, from the spatial object we build a weighted network, where the assessed risk of each segment is used as a weight. We study the topology structure of the graph and we show how classical network indicators can provide meaningful insights about the risk of an area.