Multi-objective optimization control of dynamic heterogeneous vehicle platoons based on distributed model predictive control

Vehicle platoon transportation stands poised to effectively bolster both the safety and efficiency of vehicles, thereby mitigating traffic congestion and curtailing pollution. Nevertheless, the presence of heterogeneity and the dynamic nature inherent in vehicle platoons present formidable challenges to their safe and efficient control. To bolster the flexibility and scalability of vehicle platoons while aligning with the safety, followability, economy, and comfort prerequisites of each vehicle within the platoon, this paper zeroes in on heterogeneous commercial vehicle platoons featuring dynamic vehicle insertion or departure, proffering a multi-objective optimization control strategy grounded in a distributed model predictive control algorithm. Initially, accounting for the disparities in the dynamic characteristics of heterogeneous vehicle platoons, a vehicle platoon model grounded in the four-element model architecture is delineated. Subsequently, a maneuvering control strategy is advanced for dynamic vehicle platoons, aiming to safeguard the flexibility, scalability, and safety of the platoon amidst dynamic vehicle insertion or departure. Subsequently, a multi-objective optimization control scheme, orchestrated between the lead and follower vehicles, is put forth, predicated on the distributed model predictive control methodology. Lastly, the effectiveness of the designed control strategy under various unidirectional topology communication scenarios is scrutinized and corroborated via collaborative simulations employing Matlab/Simulink and TruckSim. The findings underscore the efficacy of the proposed control strategy in attaining multi-objective control of dynamic vehicle platoons, thereby amplifying their flexibility and scalability.