A trust-aware edge-assisted reinforcement learning framework for secure and low-latency vehicular communication
Abstract Vehicular Ad Hoc Networks enable real-time intelligent transportation services but remain affected by dynamic mobility, unstable routing, congestion, malicious vehicles, and delayed emergency communication. This paper proposes a Trust-Aware Edge-Assisted Reinforcement Learning framework, termed TEARL-VANET, fo...