Feedforward Compensation-Based Finite-Time Traffic Flow Controller for Intelligent Connected Vehicle Subject to Sudden Velocity Changes of Leading Vehicle

Optimal velocity (OV)-based car-following model can be easily applied to the transportation system composed of intelligent connected vehicle (ICV) via vehicle-to-vehicle (V2V) communication, since this model only requires space headway and velocity differences of preceding vehicles. However, the sudden velocity changes of the leading vehicle will decrease the control performance of following vehicles. Particularly, the farther the distance between the following vehicle and the leading vehicle is, the worse the control performance of the following vehicle is. Besides this problem, the nonlinear information of OV-based car-following models is often not fully utilized due to the linearization for the convenience of stability analysis and controller design. To address these problems, the factors related to velocity sudden changes are taken into account for each ICV simultaneously and compensated by the proposed feedforward compensator. Based on the compensator, a finite-time traffic flow controller is designed for each ICV to smooth the space headway in traffic flow subject to sudden velocity changes and make full use of the nonlinear information of OV-based model. Finally, the theoretical analysis via Lyapunov approach and the numerical simulations are carried out to verify the effectiveness of the proposed method.