String Stability Based Cloud Predictive Control of Vehicle Platoon With Random Time Delay

The advancement of communication technologies significantly enhances the capabilities for cooperative control among connected vehicles. In terms of platooning, this paper proposes a delay-dependent cloud-based nonlinear model predictive control algorithm for fuel-saving platoons which requires maintaining a desired longitudinal inter-vehicle gap. Firstly, the platoon is modeled with longitudinal dynamics, considering the constraints of physical limitations and rear-end collision avoidance based on information topology. For random communication delay compensation, a delay-dependent control algorithm is designed and combined with a cloud control strategy to achieve platoon performance and improve fuel economy. This paper conducts a comprehensive analysis of the proposed method's asymptotic stability and string stability, employing Lyapunov techniques for validation. The simulation of a 10-vehicle platoon shows high tracking accuracy and quick consensus convergence as well as high fuel efficiency under the random time delay process and networked control protocol. Finally, the real-vehicle platooning test is conducted, demonstrating that the space errors are maintained within 1 m under high-speed scenarios with realistic communication delays.