Autonomous Vehicle Safety
Developing with NVIDIA Halos enables vehicle safety across all levels of automation.
Overview
Autonomous Vehicle Safety, From the Cloud to the Car
NVIDIA Halos is a full-stack comprehensive safety system that unifies vehicle architecture, AI models, chips, software, tools, and services to ensure the safe development of autonomous vehicles (AVs) from cloud to car.
The system ensures safety across the full development lifecycle with design-time, deployment-time, and validation-time guardrails that collectively build safety and explainability into AI-based AV stacks. These guardrails are implemented using three powerful computers—NVIDIA DGX™ for AI training, NVIDIA Omniverse™ and Cosmos™ for simulation, and NVIDIA AGX™ for deployment.
NVIDIA Halos also complements existing industry-standard safety practices, while introducing unique elements for autonomous vehicles. This ensures regulatory compliance, and advances safe and reliable AV stacks, together with NVIDIA’s AI Systems Inspection Lab.
Highlights
Autonomous Vehicle Safety Leadership
NVIDIA Halos is the result of continuous investment in autonomous vehicle safety—from research to engineering to active engagement with international safety standards—validated by independent third-party assessments.
Technology
Engineered for Safety, Designed for Trust
As AV companies transition to AI-based, end-to-end architectures, NVIDIA Halos provides the critical safety foundation to ensure system-level reliability and iterative improvement for automated driving systems. This includes integration of third party-assessed hardware, software, and processes with a diverse algorithmic architecture and validation pipelines.
Benefits
A Comprehensive System for Autonomous Vehicle Safety
NVIDIA Halos helps to ensure AI-driven AV systems are safe and secure. Partners can leverage NVIDIA’s investments in AI safety to accelerate development and enhance AV reliability. NVIDIA Halos is open to developers, enabling adoption or customization of safety elements, driving the shared mission to develop safe and reliable autonomous vehicle technology.
Design-time, deployment-time, and validation-time guardrails collectively build safety and explainability into several layers of technologies spanning platform safety, AI algorithmic safety, and ecosystem safety.
At the top of the NVIDIA Halos elements sits the NVIDIA AI Systems Inspection Lab, which allows customers and ecosystem partners to verify the safe integration of their products with NVIDIA Halos elements. The lab is the first worldwide program to be accredited by ANAB for AI functional safety.
Use Cases
A Full-Stack Comprehensive Safety System
NVIDIA unifies vehicle architecture from AI models, chips, software, and tools to services for safely developing autonomous vehicles, from cloud to car. NVIDIA Halos integrates foundational models and a diverse algorithmic stack, combining classical and AI-based, end-to-end models to ensure system-level safety in the shift toward AI-driven AV architectures.
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Platform Safety
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Algorithmic Safety
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Ecosystem Safety
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AI Systems Inspection Lab
Platform Safety
A robust foundation for autonomous driving systems, including:
- A System-on-a-Chip (SoC) that’s designed for safety, with hundreds of built-in safety mechanisms.
- NVIDIA DriveOS, a safety-certified ASIL-D operating system that extends from CPU, ISP, GPU, I/O, and memory.
- A safety assessed base platform that delivers the foundational safe computer needed to enable safe systems, for all types of applications
- NVIDIA DRIVE AGX Hyperion™, a diverse hardware platform that connects the SoC, OS, and sensors in a vehicle architecture that ensures a vehicle can safely execute contingency plans if needed.
Algorithmic Safety
Algorithmic AI safety spans:
- A diverse AV stack that combines a modular stack and end-to-end AI models for algorithmic AI safety.
- Training, simulation, and validation environments that use Omniverse and Cosmos platforms to build safe AVs.
- A separate safety dataset that ensures AV performance is tested against diverse, unbiased data.
Ecosystem Safety
Building a safer AV ecosystem includes:
- Continual improvements through a safety data flywheel, which continually learns from the road how to expand the set of operational design domains for safe deployment.
- Seamless integration of physically based and diverse sensor simulation into existing workflows to safely train, test, and validate AVs with the NVIDIA Omniverse Blueprint for AV Simulation.
- Open-source data, such as the NVIDIA Physical AI Dataset, to enable critical safety research throughout the industry.
- Click here to see a growing list of partners using the NVIDIA Halos system.
AI Systems Inspection Lab
NVIDIA is the first company in the world to establish an ANSI National Accreditation Board (ANAB)-accredited AI Systems Inspection Lab, integrating functional safety, cybersecurity, AI, and regulations into a unified safety framework. The lab helps to ensure that partner system integrations meet rigorous safety and cybersecurity standards through impartial assessments.
By providing inspection reports and streamlining technical validations, the lab accelerates compliance with global safety standards for AV safety and cybersecurity. This empowers the automotive ecosystem to deploy safe, more reliable AI-driven technologies while advancing compliance with international standards.
Certification
Assessed by Experts
Independent third-party safety and cybersecurity assessments of NVIDIA Halos elements demonstrate NVIDIA’s ongoing commitment to AV safety.
Research
NVIDIA Research for Autonomous Vehicles
Our research and development have published 240+ research papers on autonomous vehicle safety.
For a list of additional AV Research papers, click here.
Partners
Partners Using NVIDIA Halos System
Leading robotaxi companies, OEMs, industry safety pioneers, mapping and simulation companies, and software and sensor providers worldwide are using the system to deliver autonomous vehicle safety at all levels of automation.
Resources
The Latest in NVIDIA Halos Resources
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News
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Sessions
Next Steps
Redefining Safe Autonomy
Learn how cutting-edge AI, rigorous validation frameworks, and global standards are shaping autonomous vehicle safety.
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