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Boosting autonomous navigation

Boosting autonomous navigation

– Article Courtesy: NVIDIA

New DRIVE PX 2 uses deep learning and supercomputing to enable cars to sense surroundings and navigate autonomously.

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Accelerating the race to autonomous cars, NVIDIA launched NVIDIA DRIVEâ„¢ PX 2, the world`s most powerful engine for in-vehicle artificial intelligence.

This allows the automotive industry to use artificial intelligence to tackle
the complexities inherent in autonomous driving. It utilises deep learning on NVIDIA`s most advanced GPUs for 360-degree situational awareness around the car, to determine precisely where
the car is and to compute a safe, comfortable trajectory.

“Drivers deal with an infinitely complex world,” said Jen-Hsun Huang, Co-founder and CEO, NVIDIA. “Modern artificial intelligence and GPU breakthroughs enable us to finally tackle the daunting challenges of self-driving cars.

“NVIDIA`s GPU is central to advances in deep learning and supercomputing. We are leveraging these to create the brain of future autonomous vehicles that will be continuously alert, and eventually achieve superhuman levels of situational awareness. Autonomous cars will bring increased safety, new convenient mobility services and even beautiful urban designs – providing a powerful force for a better future.”

24 trillion deep learning
operations per second

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Created to address the needs of NVIDIA`s automotive partners for an open development platform, DRIVE PX 2 provides unprecedented amounts of processing power for deep learning, equivalent to that of 150 MacBook Pros.

Its two next-generation Tegra® processors plus two next-generation discrete GPUs based on the Pascal™ architecture, deliver up to 24 trillion deep learning operations per second, which are specialised instructions that accelerate the math used in deep learning network inference. That is over 10 times more computational horsepower than the previous-generation product.

DRIVE PX 2`s deep learning capabilities enable it to quickly learn how to address the challenges of everyday driving, such as unexpected road debris, erratic drivers and construction zones. Deep learning also addresses numerous problem areas where traditional computer vision techniques are insufficient, such as poor weather conditions like rain, snow and fog, and difficult lighting conditions like sunrise, sunset and extreme darkness.

For general purpose floating point operations, DRIVE PX 2`s multi-precision GPU architecture is capable of up to 8 trillion operations per second. That is over four times more than the previous-generation product. This enables partners to address the full breadth of autonomous driving algorithms, including sensor fusion, localisation and path planning. It also provides high-precision compute when needed for layers of deep learning networks.

Deep learning in self-driving cars

Self-driving cars use a broad spectrum of sensors to understand their surroundings. DRIVE PX 2 can process the inputs of 12 video cameras, plus lidar, radar and ultrasonic sensors. It fuses them to accurately detect objects, identify them, determine where the car is relative to the world around it, and then calculate its optimal path for safe travel. This complex work is facilitated by NVIDIA DriveWorksâ„¢, a suite of software tools, libraries and modules that accelerates development and testing of autonomous vehicles. DriveWorks enables sensor calibration, acquisition of surround data, synchronisation, recording and then processing streams of sensor data through a complex pipeline of algorithms running on all of the DRIVE PX 2`s specialised and general-purpose processors. Software modules are included for
every aspect of the autonomous driving pipeline, from object detection, classification and segmentation to map localisation and path planning.

End-to-end solution for deep learning

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NVIDIA delivers an end-to-end solution – consisting of NVIDIA DIGITSâ„¢ and DRIVE PX 2 – for both training a deep neural network, as well as deploying the output of that network in a car.

DIGITS is a tool for developing, training and visualising deep neural networks that can run on any NVIDIA GPU-based system – from PCs and supercomputers to Amazon Web Services and the recently announced Facebook Big Sur Open Rack-compatible hardware. The trained neural net model runs on NVIDIA DRIVE PX 2 within the car.

Strong market adoption

Since NVIDIA delivered the first-generation DRIVE PX last summer, more than 50 automakers, tier 1 suppliers, developers and research institutions have adopted NVIDIA`s AI platform for autonomous driving development. The DRIVE PX 2 development engine will be generally available in the fourth quarter of 2016. Availability to early access development partners will be in the second quarter.

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