HT-DRIVE: Heterogeneous-Temporal GNN-Aided Multi-Agent Reinforcement Learning for Resource Allocation in Platoon-Based V2X Networks

Platoon-based Vehicle-to-Everything (V2X) is a promising communication paradigm for intelligent vehicular networks. In such networks, each platoon leader (PL) engages in a high-throughput vehicle-to-infrastructure (V2I) link to deliver entertainment data, while maintaining low-latency and high-reliability vehicle-to-vehicle (V2V) links with multiple platoon members (PMs) to convey safety-critical information, thus posing conflicting performance requirements. Besides, the temporal variations and