NVIDIA DriveOS™ is an automotive operating system developed with industry-standard safety and security methodologies certified by TÜV SÜD. This powerful platform is designed to meet cutting-edge automotive product requirements, including advanced AI inference, high-performance computer vision, advanced graphics, high-end audio, and complex safety and security use cases. DriveOS also supports autonomous driving and AI-powered cockpit experiences. DriveOS enables Linux or QNX as the application operating system with a software development kit for image processing, diverse sensor integration, AI acceleration, low-overhead interprocess communication, and developer tools for debugging and profiling.

Features

• Programmability: Enables a smooth transition from cloud or workstation to the SoC. Supports NVIDIA® CUDA® and TensorRT®, widely adopted programming models with a large developer base. Supports unified APIs, from cloud to target.
• Safety and Reliability: Designed for safety-critical applications. Complies with ASPICE, ISO 26262, and ISO/SAE 21434. Supports heterogeneous redundancy for compute workloads.
• Highly Optimized: Efficient processing of time-critical workloads. Camera frames are directly loaded into GPU memory for high-performance sensor interfacing and processing with NvMedia. Supports NvStreams for efficient data transport, with zero-copy data transfer between hardware accelerators. Enables highly flexible sensor-processing pipelines.
• Accelerated Application Development: Building blocks and tools for automotive software. DriveWorks provides optimized algorithms and tools. NVIDIA Nsight provides tools for debugging, profiling, and tracing. Offers rich documentation including numerous samples to demonstrate features, webinars, and GTC talks to get familiar with DriveOS.
• Virtualization and Containerization: Comprehensive scalability and isolation features. Hypervisor manages resources and provides abstraction between underlying hardware and OS on top. Guest operating systems provide additional isolation and redundancy. Host and target side Docker container support enable efficient development.

Benefits

• AI and Autonomous Driving: Supports advanced AI inference and autonomous driving applications.
• Safety Compliance: Meets industry safety standards, ensuring reliability for critical applications.
• Optimized Performance: High efficiency in processing time-critical workloads and sensor data.
• Developer Support: Comprehensive tools and documentation for accelerated application development.
• Scalability and Isolation: Enhanced scalability and isolation through virtualization and containerization.