The shift to end-to-end planning models for powering autonomous vehicles (AVs) is increasing the demand for high-quality, physically-based sensor data. These models must have a general understanding of multi-modal datasets, along with the relationships between sensor datasets, vehicle trajectories, and driving actions to help with downstream training and validation tasks. By adapting and post…
]]>Autonomous vehicle (AV) stacks are evolving from a hierarchy of discrete building blocks to end-to-end architectures built on foundation models. This transition demands an AV data flywheel to generate synthetic data and augment sensor datasets, address coverage gaps and, and ultimately, build a validation toolchain to safely develop and deploy autonomous vehicles. In this blog post…
]]>Much of the communication between drivers goes beyond turn signals and brake lights. Motioning another car to proceed, looking over to see if another driver is paying attention—even the friendly Jeep wave—all rely on human-based communication rather than vehicle technology. As autonomous vehicles (AV) must coexist with human drivers for the foreseeable future, they must be able to interpret…
]]>Intelligent interiors are transforming transportation.
]]>Autonomous trucks are commercial vehicles that use AI to automate everything from shipping yard operations to long-haul deliveries.
]]>The future is autonomous, and AI is already transforming the transportation industry. But what exactly is an autonomous vehicle and how does it work? Autonomous vehicles are born in the data center. They require a combination of sensors, high-performance hardware, software, and high-definition mapping to operate without a human at the wheel. While the concept of this technology has existed…
]]>Autonomous vehicle developers now have access to flexible, scalable, and high-performance hardware and software to build the next generation of safer, more efficient transportation. NVIDIA DRIVE AGX Orin Developer Kit is now available for general access. Powered by a single Orin system-on-a-chip (SoC), the AI compute platform includes the hardware, software, and sample applications needed to…
]]>Explore design principles for efficient transformers in production and how innovative model design can help achieve better accuracy in AV perception.
]]>NVIDIA DriveWorks 4.0 SDK is now available on the NVIDIA DRIVE Developer Download page, providing you with the latest middleware and development environment purpose-built for autonomous vehicles. NVIDIA DriveWorks provides middleware functions on top of NVIDIA DRIVE OS that are fundamental to autonomous vehicle development. These consist of the sensor abstraction layer (SAL) and sensor…
]]>This November, don’t miss the opportunity to peek inside the NVIDIA DRIVE development process. NVIDIA DRIVE solutions span from end-to-end—they are the tools NVIDIA engineers themselves use to build autonomous vehicle technology. Which is why, at NVIDIA GTC, developers have the chance to learn the latest features and how they can be applied to AV development from NVIDIA experts.
]]>NVIDIA DRIVE OS 5.2.6 Linux SDK is now available on the NVIDIA DRIVE Developer site, providing developers with the latest operating system and development environment purpose-built for autonomous vehicles. As the foundation of the NVIDIA DRIVE SDK, NVIDIA DRIVE OS is designed specifically for accelerated computing and artificial intelligence. It includes NVIDIA CUDA for efficient parallel…
]]>With NVIDIA DriveWorks SDK, autonomous vehicles can bring their understanding of the world to a new dimension. The SDK enables autonomous vehicle developers to easily process three-dimensional lidar data and apply it to specific tasks, such as perception or localization. You can learn how to implement this critical toolkit in our expert-led webinar, Point Cloud Processing on DriveWorks, Aug. 25.
]]>The annual DRIVE Developer Days was held during GTC 2021, featuring a series of specialized sessions on autonomous vehicle hardware and software, including perception, mapping, simulation and more, all led by NVIDIA experts. These sessions are now available to view anytime with NVIDIA On-Demand. The developer resources listed below are exclusively available to NVIDIA Developer Program members.
]]>This year, everyone can learn how to develop safe, robust autonomous vehicles on NVIDIA DRIVE. The annual DRIVE Developer Days is taking place April 20-22 during GTC 2021, featuring a series of specialized sessions on autonomous vehicle hardware and software, including perception, mapping, simulation and more, all led by NVIDIA experts. And now, registration is free and open to all.
]]>Autonomous vehicles are born in the data center, and at GTC 2021, attendees can learn exactly how high-performance compute is vital to developing, training, testing and validating the next generation of transportation. The NVIDIA GPU Technology Conference returns to the virtual stage April 12-16, featuring autonomous vehicle leaders in a range of talks, panels and virtual networking events.
]]>Driver assistance technology is an incredibly active research domain, from supervised assistance functions all the way to fully autonomous driving. The best way to showcase the capabilities of novel AV approaches is to demonstrate them in a real car, but there are significant challenges to this type of deployment. Getting to the point where a new approach for multi-agent prediction…
]]>When it comes to autonomous vehicle development, to ensure the highest level of safety, one of the most important areas of evaluation is performance. High-performance, energy-efficient compute enables developers to balance the complexity, accuracy and resource consumption of the deep neural networks (DNN) that run in the vehicle. Getting the most out of hardware computing power requires…
]]>You asked, we listened: DRIVE OS and DriveWorks releases are now available on NVIDIA DRIVE Developer, providing DRIVE OS users access to DriveWorks middleware and even more updates. With these releases, developers have access to the latest DRIVE OS and DriveWorks software for autonomous vehicle development, including new features, without having to wait for DRIVE Software updates.
]]>This post is the third in a series on Autonomous Driving at Scale, developed with Tata Consultancy Services (TCS). The previous posts provided a general overview of deep learning inference for object detection and covered the object detection inference process and object detection metrics. In this post, we conclude with a brief look at the optimization techniques and deployment of an end-to-end…
]]>This post is the second in a series on Autonomous Driving at Scale, developed with Tata Consultancy Services (TCS). The previous post in this series provided a general overview of the deep learning inference for object detection. In this post, we dive deep into the object detection inference process. We cover an explanation of the object detection metrics and how to interpret them with empirical…
]]>This post is the first in a series on Autonomous Driving at Scale, developed with Tata Consultancy Services (TCS). In this post, we provide a general overview of the deep learning inference for object detection. The next posts cover the object detection inference process and object detection metrics and optimization techniques and deployment of an end-to-end inference pipeline.
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