V2XArcSim: Evaluation of Efficient and Scalable 5G-based V2X Infrastructure Architectures

With the emergence of autonomous vehicles and intelligent transportation systems, vehicular communications will play a significant role in innovating, optimizing and realizing the next generation transportation systems. However, with the rise in these intelligent transport systems, it will be necessary to have flexible, efficient, scalable, and cost-effective vehicular infrastructure in place to support these transportation systems. This work studies the existing 5G NR architectures and radio capabilities, and alternative evolved 5G architectures which can be expanded to V2X communications. A novel V2X architecture with unique characteristics and advanced capabilities is proposed. A Python-based simulator is designed, which models vehicular mobility and signaling and data traffic. All the candidate V2X architectures are studied and evaluated using the simulator. These candidate architectures are evaluated using a variety of relevant metrics including the backhaul bandwidth utilization, IP packet latency, Physical Resource Block (PRB) Utilization efficiency, end-to-end packet transmission ratio. The simulation results clearly demonstrate that the proposed novel V2X architecture provides superior performance compared to other candidate architectures and provides additional benefits of flexibility, scalability, ease of deployment on a massive scale, power efficiency, and low cost.