M. F. Mridha

Hierarchical Graph Federated Learning for Cross-Domain Intelligent Transportation Networks

Experiments demonstrate that HG-FL achieves superior performance compared to centralized, flat federated, and graph-only baselines, and highlight the framework’s scalability, robustness, and effectiveness in achieving cross-domain generalization and service-level assurance within privacy-preserving ITS environments.