Category Archives: Autonomous Vehicles

NVIDIA DRIVE™ platforms include an in-vehicle computer (DRIVE AGX) and complete reference architecture (DRIVE Hyperion™), as well as data center-hosted simulation (DRIVE Constellation™) and deep neural network (DNN) training platforms (DGX™). These platforms also include rich software developer kits (SDKs) to accelerate autonomous vehicle (AV) development.

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Accelerating Autonomous Vehicle Safety

In the field of computer vision (CV), an ongoing challenge is to build systems that can extract meaningful information from images as humans do, like distinguishing a street sign from a stop sign, or identifying lane boundaries.   … Read more
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AI Predicts Future Lane Changes of Other Drivers

In work sponsored by Toyota, University of Michigan researchers developed a deep learning framework trained on GPUs to anticipate maneuvers of other highway vehicles up to three seconds into the future, such as performing left or right lane changes or staying in the same lan … Read more
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NVIDIA Looking For World’s Best AI Startup

At the 2018 GPU Technology Conference in San Jose on March 26-29, the NVIDIA Inception virtual accelerator program will host a $1 million competition to find this year’s best AI startup across three categories: Healthcare, Autonomous Systems, and Enterpris … Read more
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Fast INT8 Inference for Autonomous Vehicles with TensorRT 3

Autonomous driving demands safety, and a high-performance computing solution to process sensor data with extreme accuracy. Researchers and developers creating deep neural networks (DNNs) for self driving must optimize their networks to ensure low-latency inference and energy efficiency. Thanks to a new Python API in NVIDIA TensorRT, this process just became easier … Read more