Marco Rapelli

Roberto Pegurri, Diego Gasco, Francesco Linsalata et al.

This paper presents VaN3Twin-the first open-source, full-stack Network Digital Twin (NDT) framework for simulating the coexistence of multiple Vehicle-to-Everything (V2X) communication technologies with accurate physical-layer modeling via ray tracing. VaN3Twin extends the ms-van3t simulator by integrating Sionna Ray Tracer (RT) in the loop, enabling high-fidelity representation of wireless propagation, including diverse Line-of-Sight (LoS) conditions with focus on LoS blockage due to other vehicles' meshes, Doppler effect, and site-dependent effects-e.g., scattering and diffraction. Unlike conventional simulation tools, the proposed framework supports realistic coexistence analysis across DSRC and C-V2X technologies operating over shared spectrum. A dedicated interference tracking module captures cross-technology interference at the time-frequency resource block level and enhances signal-to-interference-plus-noise ratio (SINR) estimation by eliminating artifacts such as the bimodal behavior induced by separate LoS/NLoS propagation models. Compared to field measurements, VaN3Twin reduces application-layer disagreement by 50% in rural and over 70% in urban environments with respect to current state-of-the-art simulation tools, demonstrating its value for scalable and accurate digital twin-based V2X coexistence simulation.

Lorenzo Farina, Federico Gavioli, Salvatore Iandolo et al.

The automotive sector is following a revolutionary path from vehicles controlled by humans to vehicles that will be fully automated, fully connected, and ultimately fully cooperative. Along this road, new cooperative algorithms and protocols will be designed and field tested, which represents a great challenge in terms of costs. In this context, in particular, moving from simulations to practical experiments requires huge investments that are not always affordable and may become a barrier in some cases. To solve this issue and provide the community with an intermediate step, we here propose the use of 1:10 scaled cooperative, autonomous, and connected mini-cars. The mini-car is equipped with a Jetson Orin board running the open Robot Operating System 2 (ROS2), sensors for autonomous operations, and a Raspberry Pi board for connectivity mounting the open source Open Stack for Car (OScar). A key aspect of the proposal is the use of OScar, which implements a full ETSI cooperative-intelligent transport systems (C-ITS) compliant stack. The feasibility and potential of the proposed platform is here demonstrated through the implementation of a case study where the Day-1 intersection collision warning (ICW) application is implemented and validated.

Lorenzo Farina, Vittorio Todisco, Federico Gavioli et al.

Cooperative driving enabled by connected and automated vehicles is expected to improve traffic efficiency and safety, particularly at intersections where traditional control mechanisms such as traffic lights introduce delays and unnecessary stops. Although cooperative intersection management algorithms have been widely studied, experimental demonstrations remain limited. This paper presents a real-time demonstration of cooperative intersection management using connected autonomous mini-cars. The testbed consists of multiple 1:10 scale vehicles equipped with autonomous driving capabilities and wireless communication modules that interact with a centralized controller responsible for scheduling their crossing of the intersection. Vehicles approaching the intersection exchange messages with the controller to set the appropriate mobility profile to traverse the intersection without stopping. The demonstration integrates autonomous driving, wireless communication, and cooperative control in a single experimental platform, providing a practical environment for validating cooperative intersection management concepts for future intelligent transportation systems.