Connected and automated vehicle platoon maintenance under communication failures

Abstract

Connected and automated vehicles (CAVs) use vehicle-to-vehicle (V2V) wireless communication to drive in platoons, which can improve traffic efficiency and reduce energy consumption. However, some vehicles in a platoon may experience communication failures for various reasons, such as packet loss, signal blocking, or damage to vehicle communication module hardware. This will result in two phenomena: the platoon communication topology will be changed, and the behavior of vehicles without communication capabilities will degenerate to that of automated vehicles (AVs). The platoon will be unstable under the influence of these two phenomena. To mitigate the impact of these two phenomena on platoons, we propose a dynamic communication topology-based CAV-following model. This model takes into account changes in communication topology in a platoon due to communication failures or perceptual errors resulting from vehicle degradation. Two core features ensure that this model is able to perform platoon maintenance under communication failure. First, the CAVs in a platoon dynamically adjust the weight values of the acquired driving information based on the communication topology. Second, an adaptive Kalman filter (AKF) method is applied to reduce perceptual error. The effectiveness of the platoon maintenance scheme proposed in this study is verified by a series of simulation experiments. The results show that the proposed model can effectively maintain CAV platoons regardless of communication failures under steady-state or non-steady-state traffic flows. This finding indicates that CAV designers should design control schemes that take into account possible changes in the communication topology. Furthermore, our method has potential advantages for improving the platoon stability of CAVs driving on roads where communication is poor.