A suitable control architecture for connected vehicle platoons may be seen as a promising solution for today’s traffic problems, by improving road safety and traffic flow, reducing emissions and fuel consumption, and increasing driver comfort. This paper provides a comprehensive overview concerning the defining levels of a general control architecture for connected vehicle platoons, intending to illustrate the options available in terms of sensor technologies, in-vehicle networks, vehicular communication, and control solutions. Moreover, starting from the proposed control architecture, a solution that implements a Cooperative Adaptive Cruise Control (CACC) functionality for a vehicle platoon is designed. Also, two control algorithms based on the distributed model-based predictive control (DMPC) strategy and the feedback gain matrix method for the control level of the CACC functionality are proposed. The designed architecture was tested in a simulation scenario, and the obtained results show the control performances achieved using the proposed solutions suitable for the longitudinal dynamics of vehicle platoons.

Cellular Vehicle-to-Everything (C-V2X) technologies are to allow vehicles to exchange information with each other, with the network, but also with other road users, based on secure, reliable, and high-capacity communication links. The use of C-V2X leads to improved road safety and traffic efficiency, over-the-air software updates, pollution reduction, and remote driving, which in the end support the implementation of autonomous vehicles. The main cellular communication standards used within the C-V2X technology are the following: 4G Long-Term Evolution (LTE) and 5G New Radio (NR). This paper follows both a theoretical analysis of cellular communications in the V2X technology, through a comparative analysis of the contribution of each of them concerning the offered technical specifications, and a practical part, where various performance indicators were validated using the Simu5G simulator, which can simulate wireless communication networks and network components with a behavior close to that experienced in real-life.