Intersection Crossing in Mixed Traffic Flow Environment leveraging V2X information The paper addresses the problem of safe crossing a nonsignalized intersection in a mixed traffic scenario composed of both connected humandriven and autonomous vehicles. To solve this problem, we propose a control strategy that leverages information shared via V2X for extending the lineofsight of the onboard ranging sensors. The control protocol augments the classical IADAS approach based on local measurements with an additional networked action that has the aim of preventing oncoming colliding situations. The control strategy is purposely designed for counteracting the unavoidable presence of communication impairments that turns into multiple timevarying delays affecting the information sent via the cyberspace. The numerical analysis, carried out leveraging the MatlabSimulink platform, discloses the effectiveness of the approach for a challenging case where vehicles dynamic conditions are such that collisions would have occurred at the intersection if the vehicle would only be equipped with range sensors.

Toward a V2Ibased Solution for Traffic Lights Optimization The demographic trends and the consequent increase of urbanization lead us to answer to the growing need for mobility, by ensuring high levels of safety and travel comfort, as well as consumption reduction. In this regard, the optimal design of traffic light settings plays a fundamental role in the definition of solutions to achieve a safe and sustainable mobility in urban environments. The efficient operation of the traffic light network involves different approaches that can be classified in terms of the considered network configuration, modelling framework and strategy. In this paper, a vehicletoinfrastructure (V2I) cooperation for traffic management is considered, in order to maximize the intersection capacity. Thus, the flow variability detected through V2I communications is taken into account by the responsive traffic light plans. The proposed strategy is compared with a video analyticsbased solution performed by cameras monitoring the intersection, with the aim to evaluate the performance robustness of both camera and V2Ibased approaches. Our numerical results reveal that outdoor conditions severely impact the quality of camerainformation inferred from the captured images, while V2Ibased solution is able to achieve better performances in terms of intersection capacity. A Channel occupancy evaluation is also conducted in order to further validate the proposed solution.