Distributed Mobility Computing Fabric & Edge Federations

MobilityCompute federates the unused supercomputing potential of idling vehicles into an edge grid. By pooling multi-teraflop NPUs and GPUs across parked and moving cars, it runs massive collective perception models and localized environmental mapping without heavy cloud datacenter dependency.

Tapping the Enormous Unused Teraflops Sitting in Urban Parking Lots

A modern electric vehicle carries up to 1,000 TOPS of neural processing power, yet utilizes less than 5% of this capacity while parked in driveways and commercial garages. MobilityCompute creates a decentralized, zero-trust compute marketplace: parked vehicles perform distributed video rendering, citywide traffic model simulations, and generative world modeling while plugged into charging stations.

Core Engineering Areas

• P2P Collaborative Perception — Exchanging intermediate neural feature maps over high-bandwidth direct sidelinks, allowing a lead vehicle to see obstacles occluded behind a following bus.
• Parked Fleet Edge Grid — Harvesting idle NPU cycles while vehicles charge overnight to process petabytes of raw road video collected during daytime operations.
• Proof-of-Compute Accounting — Vehicles submit mathematical zero-knowledge proofs proving that neural network inferences were executed faithfully without forging computation steps.

Technical Articles

• Collaborative Perception: Fusing Multi-Vehicle BEV Features in Real Time
• Engineering Parked EV Fleet Distributed Compute Clouds

Related Cluster Architecture Specifications

• AutomotiveSDV — Full SDV Stack & Reference Architecture
• A2HCard — Agent-to-Human (A2H) Interface Cards & In-Cabin Autonomous Interaction Manifests
• A2HumanCard — Standardized In-Vehicle AI Agent Capability Discovery, Trust & Authorization Cards
• AIDrivenSynBio — AI-Driven Synthetic Biology for Automotive In-Cabin Air Purification, Bio-Engineered Pathogen Scavengers & Molecular Biosensors