• Energy Research

The purpose of this study is to determine the safety effectiveness of an intervention on an existing road by using predictive methods. Predictive methods allow the benefit of the intervention to be quantified in terms of crash reduction. Currently, the most widely used model is reported in the Highway Safety Manual, developed in the US. The HSM model is adapted to the Italian context through a calibration procedure. The model is then applied to two future scenarios: in the absence and presence of intervention. The redesign intervention consists of rehabilitating some road sections and constructing five tunnel bypasses to avoid crossing residential areas. The comparison between the ‘with’ and ‘without’ scenario estimated an overall reduction in the number of accidents of around 45%. The variant scenario is based on reasonable assumptions that allowed the determination of the proportion of traffic that will be diverted to the variant. In addition, several alternative future scenarios are considered to assess a possible different trend in assumed traffic distribution. Moreover, a possible overall increase or reduction in total traffic affecting the road is taken into account. The results showed that the intervention provided significant benefits even with increased traffic, proving the resilience of the intervention.

The use of Electric Vehicles (EV) seems to be a promising solution to achieve a sustainable road transport system. Among the contactless dynamic vehicle charging technologies, the use of Charging Units (CUs)—cement concrete box—embedded into the road pavement seems to be a favorable option. The available scientific papers related to the structural effects of embedding CUs in road pavements consider the CU as a solid box, even if a cavity is needed for the electrical technologies’ accommodation. This is why the current research is aimed at studying electrified roads (e-road) with different CU cavity shapes and dimensions. In detail, pavement structural responses are investigated, as a first step, adopting a Finite Element Model (FEM), and, as a second step, the long-term performances (fatigue cracking/rutting proneness) are evaluated. The study is divided into two phases: the theoretical fatigue/rutting assessment, which allows to calculate the critical load repetitions leading to pavement failure, and an urban case study with the goals of both assessing the theoretical results and computing fatigue/rutting performance with real scale traffic conditions. The outcomes demonstrate that CUs can be used with no significant impacts on the long-term road pavement structural performance, laying the foundation for a future upgrading of the existing urban road networks.

To achieve sustainable development in the road sector, the use of Electric Vehicles (EVs) appears as a positive response to transport emissions. Among the available technologies, dynamic charging seems to overcome the main weakness points of EVs, even if it requires that traditional roads (t-roads) be equipped with a system providing electricity for EVs. Thus, so-called electrified roads (e-roads) must be implemented into the urban road networks. Since it is not possible to electrify all roads simultaneously, and also to 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 useful for 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 also verified by its application on the urban area of Milan (Italy).