Cooperative Adaptive Cruise Control for a Platoon of Connected and Autonomous Vehicles Considering Dynamic Information Flow Topology
This work addresses the practical issue of unreliable V2V communications for CAV platoons, offering a more robust control strategy.
The paper introduces a Cooperative Adaptive Cruise Control (CACC) design that adapts to dynamic information flow topologies due to communication failures in connected autonomous vehicle platoons. The proposed method maintains string stability and outperforms fixed-topology CACC in numerical experiments using NGSIM data.
Vehicle-to-vehicle communications can be unreliable as interference causes communication failures. Thereby, the information flow topology for a platoon of Connected Autonomous Vehicles (CAVs) can vary dynamically. This limits existing Cooperative Adaptive Cruise Control (CACC) strategies as most of them assume a fixed information flow topology (IFT). To address this problem, we introduce a CACC design that considers a dynamic information flow topology (CACC-DIFT) for CAV platoons. An adaptive Proportional-Derivative (PD) controller under a two-predecessor-following IFT is proposed to reduce the negative effects when communication failures occur. The PD controller parameters are determined to ensure the string stability of the platoon. Further, the designed controller also factors the performance of individual vehicles. Hence, when communication failure occurs, the system will switch to a certain type of CACC instead of degenerating to adaptive cruise control, which improves the control performance considerably. The effectiveness of the proposed CACC-DIFT is validated through numerical experiments based on NGSIM field data. Results indicate that the proposed CACC-DIFT design outperforms a CACC with a predetermined information flow topology.