Cloud/Edge-Based Cooperative Adaptive Cruise Control with Delay Compensation and Decentralized Backup

Abstract

Cooperative Adaptive Cruise Control (CACC) leverages Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication in the control synthesis, enhancing platoon safety and coordination. This work develops an error-dynamics-based control framework that incorporates nonlinear aerodynamic drag and linear rolling resistance for both centralized and decentralized CACC. The centralized controller is augmented with networked predictive control to compensate communication delays and packet loss by predicting future states and transmitting time-stamped control sequences. The decentralized controller serves as a backup mode under degraded communication, relying on delayed predecessor data without delay compensation. A delay-dependent switching strategy transitions between centralized, blended, and decentralized modes during communication failures and employs estimator-state sharing to prevent drift during mode transitions. Simulation results demonstrate that centralized with delay compensation minimizes spacing and velocity errors compared to decentralized, while the hybrid framework ensures reliable operation under adverse delay conditions.