The AECC white paper outlines how digital twins—high-fidelity digital replicas of vehicles, roads, drivers, and environments—can enable advanced automotive services. Use cases include traffic engineering via road event twins, vehicle GPU resource sharing for edge AI, and personalized adaptive cruise assist using driver behavior twins. Edge computing ensures low latency, high fidelity, and efficient data transport, while leveraging far-edge devices for cost-effective AI deployment. Challenges involve dynamic network architecture, distributed computing/storage, and orchestrating AI models. Success requires reliable, scalable infrastructure to process and act on real-time mobility data.

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