Developing a Distributed Consensus-Based Cooperative Adaptive Cruise Control (CACC) System

Autopilot driving and autonomous driving have become increasingly popular in recent years. As an example, a Cooperative Adaptive Cruise Control (CACC) system allows autopilot or autonomous vehicles to communicate with each other, and coordinate their maneuvers in a form of platoon, where one vehicle follows another with a constant velocity and/or time headway. A CACC system brings about several benefits, including the improvement of driving safety on a highway, the increase of roadway capacity, and the decrease of fuel consumption and pollutant emissions. In this paper, we propose a novel CACC system based on the distributed consensus theory, where distributed consensus algorithm and protocol are designed for platoon formation, merging maneuvers, and splitting maneuvers. Unlike many existing CACC systems, our system only uses local cooperation to achieve a global goal, hence the communication complexity is reduced. Moreover, different from most studies assuming the type and dynamics of all the vehicles in a platoon to be homogenous, our distributed consensus algorithm takes into account the length and braking ability of different vehicles. Communication delay is also included in the algorithm, making the system more realistic and applicable. A simulation study is conducted under different scenarios, including normal platoon formation, platoon restoration from disturbances, and merging and splitting maneuvers. We also carry out sensitivity analysis on the distributed consensus algorithm, investigating the effect of the damping term on driving safety and driving comfort of our CACC system.