As the automotive industry accelerates towards high levels of autonomy, the demand for real time, safety critical control systems continue to grow. High-performance computing like NVIDIA Drive Orin plays a central role in enabling real time decision-making at the edge. To address these challenges, our engineering team build series of ADAS use cases leveraging NVIDIA DRIVE Orin™, a powerful AI-enabled SoC using DriveWorks SDK.

With its automotive-grade reliability and unmatched compute performance, DRIVE Orin™ offers the scalability required to handle complex perception, sensor fusion, and deep learning workloads, delivering up to 254 TOPS for AI-based vehicle functions.

This white paper is focused on building real world use cases like vehicle, pedestrian detection, lane detection, LiDAR point cloud processing, driver drowsiness monitoring and vehicle localization. Each use case was optimized to run in real time, leveraging Orin’s compute resources – CPU, GPU, DLA to maximize performance while meeting low latency requirements of ADAS applications.

Our work serves as a reference for the customers looking to accelerate their development on NVIDIA DRIVE Orin™ and leverage our experience to reduce integration time for building ADAS/AV solutions. This paper can act as a guide to optimize performance using NVIDIA’s full software stack, including CUDA, TensorRT, and the DriveWorks SDK for complete ADAS pipeline.