Platoon Control Leveraging Network Performance and State Estimation Under Dynamic V2V Network

This paper presents a distributed platoon control method designed to mitigate the impact of dynamic network interruptions on vehicle platoon safety and stability. Such interruptions pose significant challenges to maintaining platoon formation and achieving effective tracking performance. The proposed approach integrates network performance and state estimation within a nonlinear distributed model predictive control (DMPC) framework. A V2V communication model for platooning on straight roads is developed using stochastic geometry theory, and a unidirectional connectivity determination method assesses platoon topology connectivity. Missing information due to communication degradation is estimated using the probabilities of successful V2X information reception and connectivity results. This estimation provides reference trajectories for disconnected vehicles, ensuring platoon safety and stability. The performance of the proposed method is evaluated through simulations of a heterogeneous platoon with 15 vehicles under nine network topologies, considering both fixed-time and random intermittent network interruptions. Results demonstrate that under random network interruptions, the proposed method improves tracking performance by 87.1%, driving comfort by 72.5%, and energy efficiency by 23.2% compared to a baseline control method. Preliminary real-world testing further validates the feasibility of the approach. These findings underscore the effectiveness of the proposed method in maintaining platoon stability and safety, even during complete V2X communication loss.