Joint Communication and Control Optimization of a UAV-Assisted Multi-Vehicle Platooning System in Uncertain Communication Environment.

In the context of intelligent and networked transportation, vehicle platoon control technology is an essential measure for improving overall vehicle traffic efficiency, reducing driving energy consumption, increasing driver comfort and driving safety, and easing traffic congestion. However, in high-speed mobile states, vehicles face an uncertain communication environment, making it difficult to meet the demand for multi-vehicle cooperative control. To address the existing research deficiencies, this paper investigates a UAV-assisted multi-vehicle cooperative platoon system. The paper aims to improve the communication success probability between vehicles and UAV nodes while mitigating the velocity perturbations generated by the platoon during travel. Specifically, we design a platoon controller based on a discrete double integral model and a joint optimization model for resource scheduling of air-ground communication. This model can flexibly adjust the communication resource allocation of each platooning vehicle within each timeslot according to the communication link. Due to the complex coupling between the variables of the objective function and the constraints of the optimization problem, we design an optimization iterative solution method based on sequential quadratic programming (SQP). Finally, we verify the effectiveness of the proposed joint optimization method through simulation experiments compared to benchmark methods.