What NVIDIA DRIVE includes
Automated-driving systems need to process information from sensors, understand the surrounding environment, make decisions, and operate under strict safety and latency requirements.
NVIDIA develops DRIVE technologies across several layers, including:
- in-vehicle computing;
- AI software;
- development tools;
- simulation;
- data-center computing used during model development.
Why vehicles need accelerated computing
Modern vehicles can use cameras, radar, lidar, maps, and other data sources.
AI systems process this information to perform tasks such as:
- detecting objects;
- understanding lanes and road geometry;
- monitoring the driver;
- planning routes or vehicle movement;
- supporting automated-driving features.
These workloads can require substantial parallel computing.
DRIVE and simulation
Automotive AI cannot be trained and tested only on public roads.
Simulation can expose software to large numbers of controlled and unusual scenarios.
This creates a connection between NVIDIA DRIVE and Omniverse, which includes technologies used for simulation and digital twins.
DRIVE inside NVIDIA
NVIDIA reports Automotive as one of its major market platforms.
Automotive is much smaller than NVIDIA's data-center business, but it illustrates how the company applies the same broader strategy across industries:
Accelerated computing
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AI software
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Simulation
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Developer tools
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Industry-specific platformSources
- NVIDIA DRIVE documentation
- NVIDIA 2026 Form 10-K