Research on Cooperative Adaptive Cruise Control System for Autonomous Vehicles based on Distributed Model Predictive Control

As a beneficial way of increasing traffic capacity, autonomous vehicle platoons have paid extensive attention recently. This study proposes a Distributed Model Predictive Control (DMPC) algorithm with input constraints. This algorithm is a suitable application for Cooperative Adaptive Cruise Control (CACC) in the vehicle platoon. The platoon’s leading vehicle is to track an imposed velocity reference, the rest of the platoon is to track the velocity of the preceding while maintaining an imposed desired reference between any consecutive vehicles, which is proportional to its velocity. A varied communication range in the predecessor following (PF) topology is used for a platoon. The effectiveness of the proposed method is verified with some illustrative results.