A Novel Autonomous Trajectory Control for Vehicular Cyber-Physical Systems with Flocking Control Algorithms

Cooperative control of multiple autonomous ground vehicles (AGVs) with flocking algorithms has promising potential to tackle the issues of traffic congestion and accidents. This paper presents a novel method to generate predictive yaw rate references of multiple AGVs to follow path trajectories planned by flocking algorithms without utilizing tire cornering stiffness information. In addition, an analytical single-point preview driver model is proposed to serve as a feedforward controller to mitigate both longitudinal and lateral position tracking errors, together with a feedback controller designed through the Lyapunov theory. Trajectory control of five indistinctive vehicles based on flocking algorithms is studied. Demonstrated by simulations results, all the simulated vehicles can successfully achieve a flock topology without collisions and accurately track planned path trajectories and yaw rate references.