MARCH 2019CIOAPPLICATIONSEUROPE.COM8IN MYOPINIONDeveloping an AI-powered VehicleAutonomy will fundamentally improve the way the world moves -- from shared and personal vehicles, to long- and short-distance travel, to delivery and logistics. The most significant benefit of this transportation evolution is safety. Today, 94 percent of crashes are caused by human error. By removing the human driver, autonomous vehicles can prevent or mitigate the majority of traffic crashes. For self-driving cars to deliver this crucial benefit, they require a massive amount of compute performance. The more compute, the more sophisticated the algorithm, the more layers in a deep neural network can be run to enable the car to see, think and act. The computational requirements of fully autonomous driving are enormous--easily up to 100 times higher than the most advanced vehicles in production today. But the next generation of autonomous cars will not only rely on energy-efficient, high-performance hardware, it will also need sophisticated software which needs to be developed, validated and certified within the car company. Autonomous driving is more than just replacing the human driver, it's about creating an AI driver that is much safer than a human. According to RAND Corporation, to drive even 20 percent better than a human requires 11 billion miles of real-world experience. That translates to more than 500 years of nonstop driving with a fleet of 100 cars -- an impossible task. That is why a new IT infrastructure is needed to seamlessly support the development of the car, the The Future of Autonomous Transportation Requires AI Supercomputing in the Car and in the CloudSERKAN ARSLAN, DIRECTOR OF AUTOMOTIVE, NVIDIA EUdevelopment of the software stack for autonomous driving and the simulation environment to virtually test and validate the vehicle.The Next Generation of Vehicles will be Software Defined Today's car companies are experiencing a digital transformation. Cloud-to-car computing and car development by creating a digital representation of the vehicle require a completely new look at today's IT infrastructure. Software is becoming an integral part of the entire development process, from the virtual design of a car to the industrial design through the mechanical and electrical design, to autonomous driving development. The latter relies heavily on using artificial intelligence to train deep neural networks, and then exhaustive simulation to test and validate the entire hardware and software stack before putting vehicles on the road.Processes once defined by CDOs now need to be integrated into the IT department and run by the CIO. Creating a stable platform for developers amid an extremely dynamic ecosystem is crucial. Developing an end-to-end production pipeline can help ensure innovation, while not losing sight of the actual vehicle production. As the automotive industry is transitioning from hardware- to software-defined vehicles, the average software and electronics content per vehicle is rapidly increasing. Currently, the vehicle's software functions are powered by dozens of electronic control units that are distributed throughout the car. Each is specialized -- one unit controls windows and one the door locks, for example, and others control power steering and braking. By combining this into one high-performance, energy-efficient compute platform, next-gen vehicle architecture will be more capable and cost effective. Centralizing and unifying compute in the car will make it easier to integrate and update advanced software features as they become available, whether for self-
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