Predictor-Feedback CACC for Vehicular Platoons with Actuation and Communication Delays Based on a Multiple-Predecessor-Following CTH Nominal Strategy
This work addresses stability and efficiency in autonomous vehicle platoons, which is crucial for traffic management and safety, but it is incremental as it builds on existing predictor-feedback methods with a modified topology.
The paper tackles the problem of controlling vehicular platoons with actuation and communication delays by developing a predictor-feedback CACC design based on a multiple-predecessor-following topology, achieving individual vehicle stability, string stability, and zero steady-state tracking errors for any actuation delay, with simulation results showing improved traffic throughput in a ten-vehicle platoon compared to single-predecessor designs.
We develop a predictor-feedback cooperative adaptive cruise control (CACC) design relying on a multiple-predecessor-following (MPF) topology-based nominal delay-free CACC law. We consider vehicular platoons with heterogeneous vehicles, whose dynamics are described by a third-order linear system subject to actuation delay, along with vehicle-to-vehicle (V2V) communication delay. The design achieves individual vehicle stability, string stability, and zero, steady-state speed/spacing tracking errors, for any value of the actuation delay. The proofs of individual vehicle stability, string stability, and regulation rely on employment of an input-output approach on the frequency domain, capitalizing on the delay-compensating property of the design, which enables as to derive explicit string stability conditions on control and vehicle models parameters. The theoretical guarantees of string stability and the respective conditions on parameters are illustrated also numerically. We present consistent simulation results, for a ten-vehicle platoon, illustrating the potential of the design in traffic throughput improvement, as compared with a predictor-feedback CACC design in which, each ego vehicle's controller utilizes information only from a single preceding vehicle. We also present simulation results in a realistic scenario in which the leading vehicle's trajectory is obtained from NGSIM data.