Abstract:

The adoption of Electric Vehicles (EVs) appears to be a positive response to transport emissions to achieve sustainable development in the road sector. Among the available technologies, dynamic charging seems to overcome the main weak points of EVs, even if it requires that traditional roads (t-roads) be equipped with a system providing electricity for EVs. Thus, electrified roads (e-roads) must be implemented into the urban road networks. Since it is impossible to electrify all roads simultaneously and consider the demand needs of citizens, a selection criterion is essential. This research describes and develops a simple, self-explanatory, repeatable, and adaptable selection criterion aimed at helping city managers in prioritizing the roads of an urban network to be upgraded from t-road to e-road status. This method belongs to the so-called Multicriteria Spatial Decision Support Systems (MC-SDSS)—processes helpful in solving spatial problems through the integration of multicriteria analysis (Fuzzy Analytic Hierarchy Process, F-AHP) with a geo-referenced data management and analysis tool (GIS). The developed algorithm is based on several criteria related to the infrastructure/transport, social and environmental areas. The result of the implemented method is a Feasibility Index (FI), able to prioritize the roads most eligible to be upgraded as e-roads, as verified by its application in the urban area of Milan (Italy).