A Survey of Multi-Vehicle Consensus in Uncertain Networks for Autonomous Driving

Multi-agent-based cooperation of autonomous vehicles(AVs) holds the potential to improve road safety, reduce emissions, and increase transport efficiency. However, the presence of uncertainties stemming from various sources poses a risk to the communication network and can alter the network topology, potentially causing instability in the multi-vehicle system. These uncertainties originate from two main sources: internal multi-vehicle system and external traffic environment. Time delays and packet losses contribute to uncertainties within the internal multi-vehicle system due to the uncontrollability of communication quality. Additionally, the dynamic nature of traffic environments introduces uncertainties related to the number of vehicles, interaction relationships, tasks, and destinations, thereby affecting communication resources and network topologies. Consequently, it is imperative to study the uncertainties faced by the multi-agent system and explore consensus methods for addressing these uncertainties. Notably, this study represents the first comprehensive review of consensus methods for both platooning and broader multi-agent cooperation in the presence of uncertain networks. Furthermore, a systematic summary of multi-agent consensus methods is presented, explicitly addressing two aspects of network uncertainty: imperfect communication transmission and the intricacies of traffic dynamics. The conclusion provides insights into open research issues, paving the way for future studies aimed at enhancing overall multi-vehicle system performance, including aspects such as convergence rate, robustness, and resilience.