This week NVIDIA unveiled what it claims to be the world’s first artificial intelligence computer designed specifically to “drive” fully autonomous vehicles.
The new system, codenamed Pegasus, brings the NVIDIA® DRIVE™ PX AI computing platform for handling Level 5 driverless vehicles (Level 5 is ”steering wheel optional.” In other words, no human intervention is required, for example, a robotic taxi). NVIDIA DRIVE PX Pegasus can perform over 320 trillion operations per second — more than 10x the performance of its predecessor, NVIDIA DRIVE PX 2.
NVIDIA DRIVE PX Pegasus is intended to help make a new class of vehicles possible that can operate without a driver — fully autonomous vehicles without steering wheels, pedals, or mirrors, and interiors that feel more like a living room or office than a vehicle. They will arrive on demand to safely take passengers to their destinations, bringing mobility to everyone, including the elderly and disabled.
One of the driving forces behind autonomous vehicles is to recapture millions of hours of lost time that could be used by “drivers” (really passengers) to work, play, eat or sleep on their daily commutes. Theoretically, countless lives could be saved by vehicles that are never fatigued, impaired, or distracted — increasing road safety, reducing congestion, and possibly freeing up 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.
NVIDIA AI Vehicle Demonstration
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 with human drivers.
