Self-driving cars, Nvidia Corporation, Santa Clara, California, USA

In contrast to the usual approach to operating self-driving cars, we did not program any explicit object detection, mapping, path planning or control components into this car. Instead, the car learns on its own to create all necessary internal representations necessary to steer, simply by observing human drivers.

The car successfully navigates the construction site while freeing us from creating specialized detectors for cones or other objects present at the site. Similarly, the car can drive on the road that is overgrown with grass and bushes without the need to create a vegetation detection system. All it takes is about twenty example runs driven by humans at different times of the day. Learning to drive in these complex environments demonstrates new capabilities of deep neural networks.

The car also learns to generalize its driving behavior. This video includes a clip that shows a car that was trained only on California roads successfully driving itself in New Jersey.

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Watch the NVIDIA DRIVE Autonomous Vehicle Platform in action, with examples of deep learning perception, LIDAR perception, egomotion, localization to HD map, path planning and more.

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At CES 2018, we joined many of our partners on the show floor to learn about the latest autonomous driving innovations. For more information on our partner ecosystem, visit our website:
nvidia.com/en-us/self-driving-cars/partners

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At this year’s GPU Technology Conference, NVIDIA illustrated some of its AI building blocks for self-driving cars and an autonomous drive through city streets and onto a highway.

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This special edition DRIVE Labs episode shows how NVIDIA DRIVE AV Software combines the essential building blocks of perception, localization, and planning/control to drive autonomously on public roads around our headquarters in Santa Clara, Calif.

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The technology of Omniverse Avatar enables DRIVE Concierge to serve as everyone’s digital assistant, helping them make recommendations, book reservations, make phone calls and provide alerts — all personalized to each driver and passenger.

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DRIVE Sim uses the power of Omniverse Replicator to generate synthetic ground-truth data for training deep neural networks that make up the perception systems in autonomous vehicles. With DRIVE Sim, synthetic data has proven very effective in accelerating AV development, allowing developers to tailor ground truth data to the specific needs of the model.

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