Resilient Cooperative Control of Connected and Automated Mixed Traffic: From Effective Controllability to Network Recovery.

Connected and automated vehicles (CAVs) are emerging as mobile sensing and actuation resources in mixed traffic, but their contribution to urban road-network resilience depends on more than nominal penetration. This structured critical review examines how local CAV sensing and control can be translated into effective controllability and measurable recovery across vehicle, intersection, corridor, and network scales. An auditable pre-submission update retrieved 1601 raw records from the Web of Science Core Collection, ScienceDirect, and IEEE Xplore and yielded 1476 unique auditable candidates after deduplication. This update identified 66 incremental relevant records, which were combined with the earlier 202-study evidence pool to form a 268-record corpus for the final synthesis. The final corpus was organized into core, bridging, and background/methodological evidence and synthesized using an eight-dimensional evidence framework. The synthesis shows that effective controllability depends on CAV spatial availability, platoon organization, HDV response, communication quality, and computation latency. Signal-vehicle coordination can jointly reshape right-of-way and arrival processes, yet most studies still emphasize nominal delay, energy, throughput, or safety rather than disruption-stage service retention and recovery. We therefore synthesize a cross-scale control architecture and a communication-aware control-quality contract linking traffic and V2X states, cooperation mode, safe fallback, and re-synchronization. Service retention, cumulative performance loss, and recovery time are recommended as resilience objectives, while the E0-E4 maturity ladder highlights the remaining gap between simulation performance and deployment-ready evidence.