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Precise vehicle positioning is a key element for the development of Cooperative Intelligent Transport Systems (C-ITS). In this context, we present a distributed processing technique to augment the performance of conventional Global Navigation Satellite Systems (GNSS) exploiting Vehicle-to-anything (V2X) communication systems. We propose a method, referred to as Implicit Cooperative Positioning with Data Association (ICP-DA), where the connected vehicles detect a set of passive features in the driving environment, solve the association task by pairing them with on-board sensor measurements and cooperatively localize the features to enhance the GNSS accuracy. We adopt a belief propagation algorithm to distribute the processing over the network, and solve both the data association and localization problems locally at vehicles. Numerical results on realistic traffic networks show that the ICP-DA method is able to significantly outperform the conventional GNSS. In particular, the analysis on a real urban road infrastructure highlights the robustness of the proposed method in real-life cases where the interactions among vehicles evolve over space and time according to traffic regulation mechanisms. Performances are investigated both in conventional traffic-light regulated scenarios and self-regulated environments (as representative of future automated driving scenarios) where vehicles autonomously cross the intersections taking gap-availability decisions for avoiding collisions. The analysis shows how the mutual coordination in platoons of vehicles eases the cooperation process and increases the positioning performance.

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This study presents a method for analysing the traffic and electric performance of wireless Charge While Driving (CWD) systems for two types of electric vehicle: a light-van for freight distribution and a city car. After performing a preliminary design of the CWD system, a simplified traffic simulation, including an energy assessment for vehicles, is presented to test the design settings, such as the travelling speed on CWD and the percentage of equipped lanes. The speed range explored refers to quite low values because the design layout of the EVSE should be a compromise between the need to minimize the installation and maintenance costs and users' acceptance of the time required to obtain a proper recharge. The choice of the traffic modelling approach derives from the specific requirements of the CWD system defined in the eCo-FEV project, which may be assumed as having been installed along a low speed lane of a motorway. The simplified traffic model simulates the vehicles time series along the road, introducing their energy needs as an influencing factor of drivers' behaviour. The simulated scenarios involve electric light-vans travelling along a 5-km highway that have the opportunity to charge in motion if their State of Charge (SOC) is under an established threshold.

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