Efficient Robust Model Predictive Control for Behaviorally Stable Vehicle Platoons

With increasing emphasis on vehicular automation and traffic efficiency, the management and coordination of platoon-based systems have become important. This research introduces a unique control framework based on a behavioral stability strategy, designed to enhance the cohesion of vehicle platoons and improve their ability to resist disturbances. Our approach integrates a vehicle scheduling system with a real-time platoon control mechanism to enhance the behavioral stability, robustness, and safety of the platoon. Given the heterogeneous nature of vehicles, we propose an optimal platoon formation model. This model strategically determines the number of platoons, arranges the sequence of vehicles within each platoon, and selects optimal cruising speeds to maximize platoon cohesion. To further enhance system robustness, a centralized robust model predictive controller is deployed for each platoon, ensuring stability against stochastic perturbations in vehicle dynamics and guaranteeing platoon safety. Finally, we conduct a simulation study involving multiple platoons with 20 heterogeneous vehicles to validate the effectiveness of the multi-layer optimization model.