Autonomous Vehicle Simulation

Explore high-fidelity sensor simulation for safe autonomous vehicle development.

Workloads

Simulation / Modeling / Design

Industries

Automotive and Transportation

Business Goal

Return on Investment
Risk Mitigation

Products

NVIDIA Omniverse Enterprise
NVIDIA OVX
NVIDIA DGX

The Need for High-Fidelity AV Simulation

Simulation is crucial for developing and validating safety-critical features in autonomous vehicles (AVs), but it requires extensive testing before deployment. High-fidelity simulation provides a safe, controlled, and realistic environment for training AV systems across various scenarios. This technology effectively simulates real-world conditions, allowing for vehicles' safe testing and validation through a digital twin before they’re road-ready.

Why AV Simulation Matters:

Safety First

Accurately model diverse driving conditions such as adverse weather, traffic changes, and rare or dangerous scenarios.

Cost Efficiency

Use virtual testing to cut development and validation costs by minimizing physical tests.

Scalability and Flexibility

Deploy a virtual fleet to prototype new sensors and stacks before any physical prototyping.

Running Physically Accurate AV Simulation At Scale

NVIDIA Omniverse™ Cloud APIs for Autonomous Vehicle Simulation, built on OpenUSD and NVIDIA RTX™, are designed to let sim developers enhance their AV simulation workflows with high-fidelity sensor simulation, physics, and realistic behavior. With these APIs, you can connect to a vast ecosystem of partners building simulation tools for vehicle dynamics and traffic. You can also bring in USD content to expand to new locales and tackle new operational design domains (ODDs).

Sensor RTX Microservices enable physically based and neural rendering of sensors commonly deployed on autonomous vehicles, including cameras, lidar, radar, and ultrasonics sensors. The rendered synthetic data and ground-truth labels can be used for training perception models and validating the AV software stack in closed-loop testing.

Autonomous Vehicle Sensor Simulation, Powered by Omniverse Cloud APIs

See how Foretellix uses NVIDIA Omniverse Cloud APIs to generate high-fidelity sensor simulation for autonomous vehicle development.

Tap into a shared ecosystem of compatible simulation-ready content.

Quickly expand Omniverse Cloud AV Simulation V&V capabilities by connecting to Foretellix's coverage-driven validation platform Foretify™.

Rapidly import environments into Omniverse Cloud with MathWorks RoadRunner.

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News

NVIDIA Supercharges Autonomous System Development With Omniverse Cloud APIs

NVIDIA Omniverse Cloud APIs are designed to address this challenge by delivering large-scale, high-fidelity sensor simulation.

NVIDIA Research Wins CVPR Autonomous Grand Challenge for End-to-End Driving

NVIDIA was named an Autonomous Grand Challenge winner at CVPR in the End-to-End Driving at Scale category, outperforming more than 400 entries worldwide.

End-to-End Driving at Scale with Hydra-MDP

NVIDIA introduces Hydra-MDP, an innovative framework that advances the field of end-to-end autonomous driving.

Simulating Realistic Traffic Behavior With a Bi-Level Imitation Learning AI Model

The NVIDIA Research team outlines a novel approach to simulating real-world traffic behavior that enables developers to develop and deploy systems that can operate in multiple ODDs with varying traffic behaviors.