Abstract
Platooning is one of the innovations in the automotive industry, which aims to improve the safety and efficiency of automobiles, while alleviating traffic congestion, reducing pollution, and reducing passenger pressure. According to the car-following (CF) theory, a platoon control strategy for autonomous vehicles based on sliding-mode control (SMC) theory is proposed. This strategy can be applied to achieve the rapid platoon forming of multiple autonomous vehicles and maintain the stable state of the vehicle platoon. The Multiple Velocity Difference (MVD) model is selected to describe the positional state of vehicle platoon changing over time. The control target is to converge the error between the actual headway (the distance between front tips of two neighboring cars) and the expected headway to zero while ensuring the stable velocity and acceleration of the platoon. In addition, a hypothetical first car strategy is proposed to improve the control efficiency. Numerical simulation experiments for urban roads and highways are designed, the space-time states of vehicle platoon under different MVD model parameters (non-control strategy) and sliding-mode control strategies are compared. The results show: proposed improved vehicle platoon sliding-mode control strategy can provide a shorter time of forming a platoon and better stability in the simulated environment, and its control effect is better than that of non-control strategy and conventional sliding-mode control strategy. Besides the proposed strategy allows vehicle platoon to quickly reach a stable and controllable state, and it provides an idea for collaborative control of autonomous vehicles.
Highlights
With the development and application of autonomous driving technology, vehicles are accelerating the transition from manually controlled mechanical products to intelligent products controlled by intelligent systems
Jiang et al put forward the Full Velocity Difference (FVD) Model based on the CF model, and applied it to describe the phase transition of traffic flow to estimate the congestion evolution [5]
First, we combined the classic Multiple Velocity Difference (MVD) model and an improved sliding-mode control method to realize the process that the vehicles quickly formed a stable platoon from irregular positions and speeds, and observed the performance of the platoon in continuous disturbance; second, we fully considered the drivers’ experience and traffic regulations during the formation of the platoon, limiting the speed and acceleration of the vehicles during the formation of the platoon; third, we improved the conventional sliding-mode controller, which greatly weakened the chatter and made it practical
Summary
With the development and application of autonomous driving technology, vehicles are accelerating the transition from manually controlled mechanical products to intelligent products controlled by intelligent systems. From the perspective of practical engineering, there are two important behaviors for vehicle platoon i.e., the formation and the maintenance of the platoon This process cannot be achieved by following only the CF model. First, we combined the classic MVD model and an improved sliding-mode control method to realize the process that the vehicles quickly formed a stable platoon from irregular positions and speeds, and observed the performance of the platoon in continuous disturbance; second, we fully considered the drivers’ experience and traffic regulations during the formation of the platoon, limiting the speed and acceleration of the vehicles during the formation of the platoon; third, we improved the conventional sliding-mode controller, which greatly weakened the chatter and made it practical. With the gradual popularization of autonomous driving, the proposed platoon control strategy can provide necessary scientific guidance in improving transportation efficiency and safety
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
