Tuesday, October 10th 2017
25+ Companies Developing Level 5 Robotaxis on NVIDIA CUDA GPUs
NVIDIA today unveiled the world's first artificial intelligence computer designed to drive fully autonomous robotaxis. The new system, codenamed Pegasus, extends the NVIDIA DRIVE PX AI computing platform to handle Level 5 driverless vehicles. NVIDIA DRIVE PX Pegasus delivers over 320 trillion operations per second -- more than 10x the performance of its predecessor, NVIDIA DRIVE PX 2.
NVIDIA DRIVE PX Pegasus will help make possible a new class of vehicles that can operate without a driver -- fully autonomous vehicles without steering wheels, pedals or mirrors, and interiors that feel like a living room or office. They will arrive on demand to safely whisk passengers to their destinations, bringing mobility to everyone, including the elderly and disabled.
Millions of hours of lost time will be recaptured by drivers as they work, play, eat or sleep on their daily commutes. And countless lives will be saved by vehicles that are never fatigued, impaired or distracted -- increasing road safety, reducing congestion and freeing up valuable land currently used for parking lots.
Of the 225 partners developing on the NVIDIA DRIVE PX platform, more than 25 are developing fully autonomous robotaxis using NVIDIA CUDA GPUs. Today, their trunks resemble small data centers, loaded with racks of computers with server-class NVIDIA GPUs running deep learning, computer vision and parallel computing algorithms. Their size, power demands and cost make them impractical for production vehicles.
The computational requirements of robotaxis are enormous -- perceiving the world through high-resolution, 360-degree surround cameras and lidars, localizing the vehicle within centimeter accuracy, tracking vehicles and people around the car, and planning a safe and comfortable path to the destination. All this processing must be done with multiple levels of redundancy to ensure the highest level of safety. The computing demands of driverless vehicles are easily 50 to 100 times more intensive than the most advanced cars today.
"Creating a fully self-driving car is one of society's most important endeavors -- and one of the most challenging to deliver," said Jensen Huang, NVIDIA founder and CEO. "The breakthrough AI computing performance and efficiency of Pegasus is crucial for the industry to realize this vision.
"Driverless cars will enable new ride- and car-sharing services. New types of cars will be invented, resembling offices, living rooms or hotel rooms on wheels. Travelers will simply order up the type of vehicle they want based on their destination and activities planned along the way. The future of society will be reshaped," he said.
Broad Industry Support
Virtually all carmakers, transportation as a service companies, as well as startups are using NVIDIA AI in the development of Level 5 vehicles.
"Today dozens of companies are racing to develop robotaxis, but they are still gated by the massive computation needs of a truly driverless car," said Luca De Ambroggi, senior principal automotive analyst at IHS Markit. "The new NVIDIA DRIVE PX Pegasus shows the path to production for the automakers, startups and automotive ecosystem working to deliver this amazing vision."
Product Specifications
NVIDIA DRIVE PX Pegasus is powered by four high-performance AI processors. It couples two of NVIDIA's newest Xavier system-on-a-chip processors -- featuring an embedded GPU based on the NVIDIA Volta architecture -- with two next-generation discrete GPUs with hardware created for accelerating deep learning and computer vision algorithms. The system will provide the enormous computational capability for fully autonomous vehicles in a computer the size of a license plate, drastically reducing energy consumption and cost.
Pegasus is designed for ASIL D certification -- the industry's highest safety level -- with automotive inputs/outputs, including CAN (controller area network), Flexray, 16 dedicated high-speed sensor inputs for camera, radar, lidar and ultrasonics, plus multiple 10Gbit Ethernet connectors. Its combined memory bandwidth exceeds 1 terabyte per second.
NVIDIA DRIVE PX Platform
The NVIDIA DRIVE PX platform scales from a single mobile processor configuration delivering Level 2+/Level 3 capabilities to a combination of multiple mobile processors and discrete GPUs for full Level 5. These configurations run on a single, open software architecture. This enables automakers and tier 1 suppliers to move from development into production for a wide range of self-driving solutions -- from AutoCruise on the highway, to AutoChauffeur for point-to-point travel, to Pegasus for a fully autonomous vehicle.
NVIDIA DRIVE PX is part of a broad family of NVIDIA AI computing solutions. Data scientists who train their deep neural networks in the data center on the NVIDIA DGX-1 AI supercomputer can seamlessly run on NVIDIA DRIVE PX inside the vehicle. The unified architecture enables the same NVIDIA DRIVE software algorithms, libraries and tools that run in the data center also perform inferencing in the car.
This cloud-to-car approach enables cars to receive over-the-air updates to add new features and capabilities throughout the life of a vehicle.
Availability
Pegasus will be available to NVIDIA automotive partners in the second half of 2018. NVIDIA DriveWorks software and NVIDIA DRIVE PX 2 configurations are available today for developers working on autonomous vehicles and algorithms.
NVIDIA DRIVE PX Pegasus will help make possible a new class of vehicles that can operate without a driver -- fully autonomous vehicles without steering wheels, pedals or mirrors, and interiors that feel like a living room or office. They will arrive on demand to safely whisk passengers to their destinations, bringing mobility to everyone, including the elderly and disabled.
Of the 225 partners developing on the NVIDIA DRIVE PX platform, more than 25 are developing fully autonomous robotaxis using NVIDIA CUDA GPUs. Today, their trunks resemble small data centers, loaded with racks of computers with server-class NVIDIA GPUs running deep learning, computer vision and parallel computing algorithms. Their size, power demands and cost make them impractical for production vehicles.
The computational requirements of robotaxis are enormous -- perceiving the world through high-resolution, 360-degree surround cameras and lidars, localizing the vehicle within centimeter accuracy, tracking vehicles and people around the car, and planning a safe and comfortable path to the destination. All this processing must be done with multiple levels of redundancy to ensure the highest level of safety. The computing demands of driverless vehicles are easily 50 to 100 times more intensive than the most advanced cars today.
"Creating a fully self-driving car is one of society's most important endeavors -- and one of the most challenging to deliver," said Jensen Huang, NVIDIA founder and CEO. "The breakthrough AI computing performance and efficiency of Pegasus is crucial for the industry to realize this vision.
"Driverless cars will enable new ride- and car-sharing services. New types of cars will be invented, resembling offices, living rooms or hotel rooms on wheels. Travelers will simply order up the type of vehicle they want based on their destination and activities planned along the way. The future of society will be reshaped," he said.
Broad Industry Support
Virtually all carmakers, transportation as a service companies, as well as startups are using NVIDIA AI in the development of Level 5 vehicles.
"Today dozens of companies are racing to develop robotaxis, but they are still gated by the massive computation needs of a truly driverless car," said Luca De Ambroggi, senior principal automotive analyst at IHS Markit. "The new NVIDIA DRIVE PX Pegasus shows the path to production for the automakers, startups and automotive ecosystem working to deliver this amazing vision."
Product Specifications
NVIDIA DRIVE PX Pegasus is powered by four high-performance AI processors. It couples two of NVIDIA's newest Xavier system-on-a-chip processors -- featuring an embedded GPU based on the NVIDIA Volta architecture -- with two next-generation discrete GPUs with hardware created for accelerating deep learning and computer vision algorithms. The system will provide the enormous computational capability for fully autonomous vehicles in a computer the size of a license plate, drastically reducing energy consumption and cost.
Pegasus is designed for ASIL D certification -- the industry's highest safety level -- with automotive inputs/outputs, including CAN (controller area network), Flexray, 16 dedicated high-speed sensor inputs for camera, radar, lidar and ultrasonics, plus multiple 10Gbit Ethernet connectors. Its combined memory bandwidth exceeds 1 terabyte per second.
NVIDIA DRIVE PX Platform
The NVIDIA DRIVE PX platform scales from a single mobile processor configuration delivering Level 2+/Level 3 capabilities to a combination of multiple mobile processors and discrete GPUs for full Level 5. These configurations run on a single, open software architecture. This enables automakers and tier 1 suppliers to move from development into production for a wide range of self-driving solutions -- from AutoCruise on the highway, to AutoChauffeur for point-to-point travel, to Pegasus for a fully autonomous vehicle.
NVIDIA DRIVE PX is part of a broad family of NVIDIA AI computing solutions. Data scientists who train their deep neural networks in the data center on the NVIDIA DGX-1 AI supercomputer can seamlessly run on NVIDIA DRIVE PX inside the vehicle. The unified architecture enables the same NVIDIA DRIVE software algorithms, libraries and tools that run in the data center also perform inferencing in the car.
This cloud-to-car approach enables cars to receive over-the-air updates to add new features and capabilities throughout the life of a vehicle.
Availability
Pegasus will be available to NVIDIA automotive partners in the second half of 2018. NVIDIA DriveWorks software and NVIDIA DRIVE PX 2 configurations are available today for developers working on autonomous vehicles and algorithms.
25 Comments on 25+ Companies Developing Level 5 Robotaxis on NVIDIA CUDA GPUs
Also in the news, is your older Nvidia Pilot driving into curbs.... it might be in need of an upgrade, after the latest Nvidia Pilot optimization for new cars, the oldest ones have been slowed by new software despite functioning fine, and a reminder, any changes to the software will result in your car driving you to the nearest detention facility for tampering with Nvidia DriveWorks.
1. Fly hits sensor lens
2. SYSTEM FATAL ERROR sensor input fault detected
3. Ejector seat activated
Makes me feel really comfortable! :kookoo:
I install GPS systems that drive big machines, it happens more often than you think.
Warning: AMD / ATI device detected in subsystems / cargo. Shutting all systems down.
AI assisted vehicles probably would be much safer, instead of giving them full control.
Or takes a minimal wage so it doesn't care of the people who is carrying around.
or took drugs, or was reading that message on whatsapp, or was yelling at that pirate so it didn't see that child on the crosswalk..
Or who cares of that redlight, i hate cyclists.
Or that person on the road seems cristian/gay/islamic/atheist/too brown in complexion, and i hate him...
Or i am 69 years old and still drive even if i see s**t.
I mean, there's a pretty high probability that the next driver you'll encounter on the road is a total asshole..
If 3 AI driven cars were going to wreck in a way that either all 3 passengers would get hurt, or 1 would die, 1 hurt, and 1 fine what outcome would be chosen? Who would get to make that decision? Ultimately it would be the coder, or anyone capable of cracking that system.
That said, today on my way home, a driver from Sears service was tailgating me, then impatiently cut over to the right most lane, then abruptly cut and forced himself over back to the left most lane. Mind you on that 3-lanes freeway, the speed limit was 70 mph and every car in the left most lane was already going 75 mph. I was maintaining a 2-car space behind the vehicle in front of me. The left most lane was already packed with cars. His action caused everyone from the middle, right most, middle again, and then all vehicles in front of me in the left most lane to hit his/her brakes abruptly. All that to gain 5 car spots in front of me. I almost called Sears to complain about his dangerous driving.
I don't drive as much as I did in my previous job, where my daily commute was in excess of 60 miles round trip. However, I saw driver similar to his driving every single day. Yup, every single day on US highway. I will take an autonomous vehicle over his driving any given day. That includes drunk drivers as well.
In addition, this is not the drivers software for your nVidia or AMD GPUs. The commitment to perfection is not necessary when creating the GPU drivers, and I don't care if nVidia or AMD come to me and say "No no, that is not what we commit to". Why? Because if your GPU crashes during the game, so what? No one dies. Just a restart and an annoyed user. Even Garmin/Navteq software does not require the sophistication required for autonomous vehicles.
Humans have been driving cars for more than a century now(?) I say the time has come for autonomous driving.
"what if there is this extreme situation x where a certain number of vehicles have to make a choice to save someone and let die someone".. ecc ecc
The thing is that with a machine (and even better when there only is a float of automated vehicles on the road), the behaviour of the vehicle will be calibrated to avoid these situations becoming real.
Most of these problems arise because normal humans have a pretty bad predictive capability, and they put themselves into riskful situations.
A machine will simply avoid any riskful situation, because it is programmed to do so, well before a human brain starts to understand that there will potentially be a problem.
A brain is a bad calculator that makes lots of errors.
It is good at speculation and creativity, it is bad at mechanical tasks. Driving is a mechanical task (when you're not racing) and a conscence-free program is the best driver you will find on a road.
But don't think about this as an engineer, think about it as lawyer: an accident happens and despite AI's best effort, a life is lost. A lawyer will have someone look at the decision making software and then conclude that if the condition in a "if" was different, that life could have been saved (never mind that this could in turn mean lives lost that under current circumstances wouldn't happen). How do you argue with that in court?
*insert mandatory 100 lawyer at the bottom of the ocean joke here*
Not to mention that there have been times when GPS data is incorrect. Or how about construction that somehow does not make it into the construction database for example, a bridge out? There are many points beyond the system internal to the vehicle at which humans can induce error, and I am willing to bet that those points will be the most problematic at first.
And one other thing, what happens if the system locks up while moving and there is no human override?
I think the worst period will be when, in the future, there'll be mixed traffic on the road, with many man driven cars, but also a lot of automated cars. it will be the perfect recipe for a total mess, also on the legal side.
I also think there will be a division between courts with a preference towards automation and others that will be more conservative, jurisprudence will be split in half in common law systems. As of civil law systems, like the one in my country, i think they'll remain stuck for tens of years before adapting..