Contents I. Introduction
The recent technological developments in the automotive industry and in detection and communication systems have highlighted the need to revise the definition of models for the prediction of traffic behavior and the traditional control techniques, in order to fully exploit the potential of emerging technologies. Starting from the 1950s great consideration has been devoted to the comprehension of traffic flow dynamics, in particular to the identification of the main phenomena that lead to the formation of traffic instabilities, and their localisation in time and space. Since then, a wide range of traffic flow models has been developed for different fields of application. Based on such traffic models, several traffic control strategies have been investigated to regulate traffic, ensuring a more efficient use of the road network capacity, minimising congestion and total travel delays in the system. For a complete overview of the freeway control strategies proposed in the literature, the interested reader may refer to [1]. In order to achieve the efficiency targets prescribed by a more sustainable vision of mobility, in recent years, several control strategies aimed at reducing the impact of traffic on the environmental system (see e.g. [2], [3]), as well as to improve traffic safety (see e.g. [4]) have been proposed. However, as pointed out in [5], the rapid spread of intelligent vehicles, capable of communicating with each other and with the infrastructure or even transforming themselves into tools of detention and transmission of data, has given rise to a wide range of technological applications requiring a specific modeling treatment and appropriate control measures.
