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Automotive Innovators Motoring to NVIDIA DRIVE

Automotive Innovators Motoring to NVIDIA DRIVE

Written by Danny Shapiro, NVIDIA

Automotive Innovators Motoring to NVIDIA DRIVE

Audi. BMW. Ford. Mercedes-Benz. Volvo. Some of the world’s biggest automotive names are flocking to DRIVE, our powerful engine for in-vehicle artificial intelligence.

So are a group of fast-moving, smaller innovators that are shaking up the auto industry. Companies such as ZMP, Preferred Networks and AdasWorks are using DRIVE PX to give automobiles astonishing new capabilities.

Unveiled Monday at CES 2016, in Las Vegas, DRIVE PX 2 provides supercomputer-class performance — up to 24 trillion operations per second for artificial intelligence applications — in a case the size of a shoebox.

Here’s a look at just three of the companies working with DRIVE PX:

 

Bringing Autonomous Driving to Taxis

Tokyo-based ZMP — which is working to help create autonomous taxis, among other projects — is using deep learning technology and NVIDIA DRIVE PX to dramatically improve accuracy of detection and decision-making algorithms for autonomous driving.

“ZMP is achieving remarkable results using deep neural networks on NVIDIA GPUs for pedestrian detection,” said Hisashi Taniguchi, CEO of ZMP. “We will expand our use of deep learning on NVIDIA GPUs to realize our driverless Robot Taxi service.”

 

In Gear with Toyota

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Preferred Networks is one of the best-known machine learning startups in Japan. The Tokyo-based company is working closely with Toyota — which purchased a 3% stake in Preferred Networks just a few weeks ago — to give cars autonomous driving capabilities.

With the NVIDIA deep learning platform, Preferred Networks has greatly improved performance on a variety of applications, such as image recognition for automotive and surveillance cameras, automated control of robotics, and health diagnostics, according to Preferred Networks founder Daisuke Okanohara.

“The remarkable thing is that we did it all with a single NVIDIA GPU-powered deep neural network, in a very short time,” Okanohara said.

 

Eyes on the Road

We’re also working with AdasWorks, a Budapest-based developer of artificial intelligence-based software for automated driving, to bring the power of our GPUs to Volvo Cars.

olvo will use the NVIDIA DRIVE PX 2 deep learning-based computing platform to power a fleet of 100 Volvo XC90 SUVs that will hit public roads next year, driven by actual customers as part of the the Swedish carmaker’s Drive Me autonomous-car pilot program.

AdasWorks worked with Volvo to help create a system that processes data from multiple sensors in real time to provide 360-degree detection of lanes, vehicles, pedestrians, signs and more, enabling a variety of autopilot functions.

NVIDIA DRIVE is more than just a component automakers can bolt into their cars. It’s an end-to-end solution for deep learning that includes a wide variety of tools and technologies, such as our DIGITS software for neural network training.

To see how it all comes together, visit our booth at CES. We’re in the North Hall, right in the middle of this year’s automotive action.

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Volvo XC90 To Use NVIDIA DRIVE PX 2 Computer

Jan. 5, 2016—Volvo Cars will use the NVIDIA DRIVE PX 2 deep learning- based computing engine to power a fleet of 100 Volvo XC90 SUVs starting to hit the road next year in the Swedish carmaker’s Drive Me autonomous car pilot programme, NVIDIA announced today.

Autonomous technology is an important contributor to Volvo’s Vision 2020 – its guiding principles for creating safer vehicles. This work has resulted in world-leading advancements in autonomous and semi-autonomous driving, and a new safety benchmark for the automotive industry.

“Our vision is that no one should be killed or seriously injured in a new Volvo by the year 2020,” said Marcus Rothoff, director of the Autonomous Driving Programme at Volvo Cars. “NVIDIA’s high-performance and responsive automotive platform is an important step towards our vision and perfect for our autonomous drive programme and the Drive Me project.”

 

The Volvo XC90 Drive Me Project

Volvo’s Drive Me autonomous pilot programme will equip the Volvo XC90 luxury cars with the NVIDIA DRIVE PX 2 engine, which uses deep learning to navigate the complexities of driving. The cars will operate autonomously on roads around Gothenburg, the carmaker’s hometown, and semi-autonomously elsewhere.

“Volvo’s Drive Me project is the ideal application of our DRIVE PX 2 engine and deep learning,” said Rob Csongor, vice president and general manager of Automotive at NVIDIA. “We are bringing years of work by thousands of NVIDIA engineers to help Volvo achieve its safety goals and move self-driving cars from Gothenburg to the rest of the globe.”

 

Recognising Objects Beyond Reach of Human Algorithms

The NVIDIA DRIVE PX 2 engine enables cars to utilise deep learning – a form of artificial intelligence – to recognise objects in their environment, anticipate potential threats and navigate safely. With 8 teraflops of processing power – equivalent to 250 MacBook Pros – it processes data from multiple sensors in real time, providing 360-degree detection of lanes, vehicles, pedestrians, signs and more, to enable a variety of autopilot functions.

Recent deep-learning breakthroughs have greatly enhanced computers’ ability to perceive the outside world. Using vast amounts of data and processing power, they can write software to recognise complex objects at a level beyond the reach of human-coded algorithms.

Much deep learning work is powered by NVIDIA’s supercomputing GPUs. For example, Microsoft and Google have used GPUs to create image-recognition systems that beat a well-trained human in the ImageNet Large Scale Visual Recognition Challenge. And Microsoft researchers recently trained a deep neural net that beat a human in IQ tests.

 

Map Localisation and Path Planning

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For map localisation and path planning, the system can compare real-time situational awareness with a known high-definition map, enabling it to plan a safe route and drive precisely along it, adjusting to ever-changing circumstances.

DRIVE PX 2 will also perform other critical functions such as stitching camera inputs to create a complete surround-view of the car.

Because self-driving cars require massive computing resources to interpret the data from multiple sensors, most early prototypes have contained a trunk full of computers. In contrast, DRIVE PX 2, which carries out the same functions, is the size of a tablet.

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If you like our work, you can help support our work by visiting our sponsors, participating in the Tech ARP Forums, or even donating to our fund. Any help you can render is greatly appreciated!