Formation Control for Connected and Autonomous Vehicles Based on Distributed Consensus Embedded With Risk Potential Field

Abstract

Cooperative control for multiple vehicles is a promising technology with the capability to improve traffic efficiency and fuel savings. Given its potential for both commercial and military applications, multiple unmanned vehicle formation has attracted considerable attention recently. In this paper, the use of formation control for connected and autonomous vehicles was explored and a novel distributed formation control approach was proposed. To begin, the evolution mechanism of multi-lane formation was investigated and a formation transition model based on a finite state machine was constructed. A bi-level formation control scheme was then proposed; this framework’s upper and lower levels were used to perform trajectory planning and MPC-based control, respectively. A novel trajectory planning approach was constructed by combining the distributed consensus algorithm and the potential field method. Moreover, additional acceleration constraints were imposed on the trajectory planning algorithm. Finally, three scenarios were designed to validate the proposed formation control algorithm using Webots. The results illustrate that a formation deployed with the proposed formation control algorithm can handle abnormal situations and realize consensus within 12s.

Keywords

• Connected and autonomous vehicle
• formation control
• formation behavior modeling
• distributed consensus
• risk potential field