Every year more than 1.35 million people die for road accidents and several million suffer serious injuries, which force them to live with compromised health conditions. Over the last decades, road safety research has focused on improving modelling techniques. However, due to the lack of expertise and statistical skills, such approaches might not be used by local authorities and road managers for road safety evaluation purposes. This paper proposes an operational methodology to analyze road accidents with the aim of increasing road safety. More specifically, the methodology enables to identify the most critical road segments to prioritize economic resources allocation accordingly. by using the data collected by the Road Police Department of Lombardy Region (in Italy) from 2014 to 2018, this methodology has been successfully applied to State Road 36, which is recognized as one of the busiest roads in Italy with a very high number of accidents occurring every year. The proposed methodology may support public administrations and road managers -involved in the definition and implementation of safety measures -to reduce the number of road accidents identifying and implementing prioritized interventions. Moreover, the methodology is general enough to be applied to each segment of a generic road infrastructure.

The work proposes a quantitative model to determine the transport relevance of the different sections of a road network. In this way it is possible to define priorities for single network elements' restore following relevant events such as earthquakes. The model was developed within a project with the Italian Civil Protection Department following the earthquakes occurred in central Italy in 2016. The planning and programming of the interventions arises from the need to restore in the shortest time the ordinary people mobility within the territory; in the meantime it is also necessary to guarantee the operational needs of the Civil Protection, such as the transport and construction of temporary housing for the population. The proposed model considers the development of 5 quantitative indicators to characterize the transport importance of the network links deciding the priority of the interventions. These indicators take into account, for example, the link flow, the number of paths over a link and the Origin/Destination pairs satisfied. In this way it is possible to assess the impact that the restore of a network link could have on one or more routes and generally on the whole road network. The model can be considered as a Decision Support System that can be used to plan and schedule the restore of a road network according to specific needs.

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