Platoon Control of Connected Multi-Vehicle Systems Under V2X Communications: Design and Experiments

TLDR

Platoon control of multi‑vehicle systems is studied in realistic V2X communication settings. The study proposes a new car‑following model that incorporates communication probability and develops longitudinal and lateral control algorithms for connected vehicles. The authors analyze beacon transmission probability under CSMA/CA, derive stability of the car‑following model via perturbation, design nonlinear consensus‑based longitudinal control and artificial‑function lateral control, prove convergence with Hurwitz and Lyapunov methods, assess string stability with the infinity‑norm, and validate the approach through field experiments with four CVs. Field experiments confirm the proposed method improves trajectory and velocity profiles.

Abstract

This paper focuses on platoon control of multi-vehicle systems in a realistic vehicle-to-vehicle/vehicle-to-infrastructure (V2V/V2I, or V2X) communication environment. To this end, the communication probability of the beacon transmission is analyzed based on the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism. Then, a new car-following model is proposed by considering the communication probability to capture the car-following behavior of connected vehicles (CVs) equipped with V2X communications. The stability of the proposed car-following model is analyzed using the perturbation method. In addition, a nonlinear consensus-based longitudinal control algorithm is designed by considering the interactions between CVs, and an artificial function-based lateral control algorithm is presented. The convergence of the longitudinal and lateral control algorithms is analyzed using the Hurwitz stable theorem and Lyapunov technique, respectively. Also, the string stability of the vehicular platoon is performed based on the infinity-norm method. Finally, field experiments are conducted using four CVs under the scenarios of platoon forming, vehicle merging, and vehicle diverging. The results verify the effectiveness of the proposed method in terms of the trajectory and velocity profiles.