Resilient Cooperative Adaptive Cruise Control Under Intermittent V2V Connectivity and Cyber-Physical Disturbances

Abstract

Cooperative adaptive cruise control systems depend on real-time sensor data and vehicle-to-vehicle communication to maintain safe inter-vehicle gaps. However, operational deployments face stochastic distortions in sensor measurements and time-varying communication delays that can destabilize platoons, degrade string stability, and create fairness and safety risks. This paper provides a system-level examination of stochastic cooperative adaptive cruise control with emphasis on structural trade-offs rather than algorithmic derivation. It analyzes the layered sensing, communication, control, and actuation architecture, and discusses how data distortion enters through environmental noise, occlusion, calibration drift, and adversarial interference. It further examines how communication latency interacts with control loop timing, information flow topology, and feedback gains. The analysis shows that robustness cannot be achieved solely through improved filtering or more aggressive control; it requires architectural redundancy, delay-aware coordination, graceful degradation mechanisms, and context-sensitive trust between vehicles. The paper considers cross-domain lessons from networked control, cyber-physical systems, and intelligent transportation infrastructure. It also addresses governance challenges including safety certification, liability, algorithmic fairness, privacy, and long-term infrastructure investment. Policy implications are discussed in relation to heterogeneous fleets, equity in access to cooperative automation, and the need for standards that distinguish transient performance from bounded stability. The paper argues that sustainable deployment requires a shift from deterministic performance benchmarks toward risk-aware, adaptive, and institutionally embedded control architectures.