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

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

Farhan Ullah, Khalid Mahmood, Umar Raza, Jawad Ahmad, Jenhui Chen, Rubal Jeet, et al.

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