Adaptive Split Federated Learning With Behavioral Digital Twins and Multi-Head Temporal Networks for Internet of Vehicles Security

A Dynamic Traffic Camouflage Method Based on Adversarial Machine Learning for Connected Vehicles

Xinyang Bai, Ping Dong, Xiaoya Zhang, Yuyang Zhang, Wenxuan Qiao, Hongke Zhang

BFRN-IoV: Blockchain and Fog-Enabled Route Navigation for Digital Twin-Based Internet of Vehicles

Amrendra Singh Yadav, Mihir Bhatt, Sameer Yadav, Sanjeev Kumar Dwivedi, Harish Kumar Shakya

Average-Reward Baseline Centering: A Plug-In Stabilizer for DDPG and MADDPG in C-V2X Platooning

Vasimbhai Vohra, Vinay Thumar, Hiren Mewada, Patel

Fast and reliable data exchange is essential for connected and autonomous vehicles, particularly in platooning scenarios where vehicles travel in close formation and depend on timely updates for safety and traffic efficiency. Actor–critic reinforcement learning can exhibit unstab…Read more