## 2 Cooperative V2X Traffic Surveillance: Background and Related Work  
The currently available and traditional traffic surveillance solutions usually exploit infrastructure-based detection devices such as inductive loops, pressure sensors, and traffic surveillance cameras, to be deployed on monitored roads [9]. These solutions, moreover, generally make use of a centralized architecture with a single point (typically hosted in the cloud) that gathers the global state of the vehicular traffic for the whole targeted area and uses it to make centralized predictions and decisions, then to be enforced in a distributed way via control commands to the different covered sub-areas. That has a non-negligible cost in terms of wired/wireless communication, often based on the use of cellular connectivity with expected global coverage, which leads to significant deployment and management costs [10; 11]. In parallel to the aforementioned traditional traffic surveillance solutions, we are aware of other services based on the collection of location information from connected smartphones, ad mobile apps running atop, that have expanded dramatically in the last years. Some of the most well-known examples are Google Traffic and Waze. These systems are currently primarily focused on collecting gross traffic density estimations at a certain road trunk. Those estimations are traditionally made available to registered (public) users providing the data; only recently, these players (e.g., Google) are making their information available also to city administrators and that could pave the way to their use for traffic management purposes. In this paper, we focus on vehicular communications that have the different goal of providing a precise, finer-grained, and punctual estimation of the traffic (e.g., number of cars and velocity variability) at the intersection to be used to enable advanced strategies for traffic management, e.g., for optimized traffic light management as in the COLOMBO project. More recent solutions targeted at collecting information for traffic management systems are shifting the focus on local data collection through the use of local traffic control protocols. This has the potential to eliminate the need for a centralized collection and processing point: the goals are to reduce complexity and costs associated with traffic surveillance, as well as to increase reliability and scalability of the adopted solutions, while retaining appropriate levels of quality/performance indicators, such as accuracy and precision. These less traditional proposals are exploring the possibility to actively involve the participating vehicles, their growing communication capabilities, and their on-board sensors, enabled by the significant advancements in vehicular networking (and its decreasing costs) and related standardization efforts, such as European Cooperative ITS (C-ITS) or American Dedicated Short Range Communications (DSRC) [12]. Furthermore, if compared with traditional sensors, which are prone to inaccuracy issues, require periodic maintenance, and have to be placed on every road that needs to be monitored, in principle the vision of connected vehicle collaboration can offer better accuracy and can be used to collect information in the entire road network at very limited costs.