A Dynamic Evolution Model for Decentralized Autonomous Car Clusters in a Highway Scene

Jiujun Cheng, Huiyu Sun, Zhangkai Ni, Aiguo Zhou

Abstract: Cluster evolution is a challenging problem for vehicular ad hoc network (VANET) in a highway scene with fast moving autonomous vehicles and frequent cluster topology changes. Most of the existing studies analyze the cluster evolution behavior of cluster heads (CHs), and these approaches lead to frequent changes in vehicle structure when CHs change, which easily makes the cluster unstable. In this work, we propose a decentralized autonomous car cluster dynamic evolution model. First, we define a decentralized cluster structure. Then, we analyze the cluster evolution behavior and propose a maintenance method. Next, we define eight vehicle states and their transitions. Finally, we introduce the cluster dynamic evolution model and the collaboration model. The results of extensive simulation experiments show that our method can effectively maintain the consistency of cluster consensus and improve the stability of the cluster structure compared with the centralized cluster maintenance method.