## 2 Background  
The introduction of AVs within the transport industry has become gradually effective with time, with an acceleration in the last decade. Their operations are affected by several factors, depending mainly on elements such as type of installed devices, scenarios, and country legislations; since these aspects affect the specific level of autonomy of vehicles, they heavily influence the spread of AVs.  
Depending on tools and vehicles equipment and according to the classification provided by SAE (Society of Automotive Engineers), it is possible to divide autonomous vehicles into two classes, each characterized by six levels of automation: the first class, equipped with ADS (Automated Driving Systems) which offers autonomous vehicle performances, and the latter equipped with tools for driver assistance only. Eventually, ADS sensors and the aforementioned tools allow vehicles to establish a V2I, V2V, and V2X communication that enables environment detection and, consequently, autonomous driving maneuvers. In addition to these technological systems, autonomous vehicles are equipped with LiDAR, GPS, cameras, and sensors whose performances have recently achieved high standards. In any case, autonomous vehicles still require an operational environment that facilitates the detection phases.  
For these reasons, any environment where autonomous vehicles are expected to operate must establish an information exchange activity through specific devices within the ITS (Intelligent Transport System) identified as RSU (Road Side Units). Such tools communicate with AVs so that a single vehicle can be informed about a specific roadway stretch, to perform all the appropriate interventions. Moreover, communication involves the monitoring of traffic and pavement conditions, and this system is identified as SRE (Smart Road Environment) [3]. In Figure 1, it is possible to recognize an example of how A more accurate analysis of the advantages brought by AVs can be appreciated when making a distinction among vehicle service types; vehicles are generally classified according to their load capacity, or whether they operate for public or private service. AVs' availability for private use would significantly improve urban traffic in terms of traffic management (congestion phenomena reduction) and safety, as a consequence of the high degree of precision of AVs maneuvers. Consequently, mass transit and public transport service [5,6] would increase their capacity and frequency due to the possibility of reducing the headway between mass transit AVs, as they would be able to brake promptly thanks to the high number of electronic sensors. Nowadays, several AVs are already in use for public service; similarly, AVs for private use are already on the market, although mainly of level-3 type within the SAE classification. Speaking of public transport, AVs have been introduced through the adoption of electrical minibuses with a maximum capacity of 20 passengers. Their main operational scenarios are airports, parks, and hospitals, just to name a few; generally, their maximum speed can reach 25 km/h [7]. The main real obstacle potentially slowing down the AV spread is of financial nature, as these vehicles are generally expensive for the common buyer; the minimum cost for manufacturing a single AV ranges in fact between EUR 6500 and 200,000. On the other side, AVs with their high precision performances lead to a reduction of car accidents, meaning reduced insurance fees and lower accident-related expenses [8,9].  
Autonomous vehicles represent a new business in which several automotive manufacturers and transport companies are already focusing. Figure 2 shows some of the brands that have already begun investing funds in AVs, and that are expected to strongly influence the market by 2030 [10].  
Figure 1: Example of potential SRE scenario with AVs [4].