Big data in autonomous driving - Automotive News #22
Big data in autonomous driving
By Lynnette Reese
http://electroiq.com/blog/2017/07/big-data-in-autonomous-driving/
On Wednesday, Intel Corporation’s Katherine Winter, Vice President of the Automated Driving Group, delivered a keynote that many would think is off-topic from the usual at SemiCon West: ”Big Data in Autonomous Driving.” She revealed that autonomous driving will shift the semiconductor industries’ focus to processing terra flops of data at blinding speeds with low latency. Winter stated, “A lot of the testing that’s going on today is to find what is the right level of MIPS to have the safest possible drive.” Winter addressed the need for computing power by the semiconductor industry to meet the challenges that autonomous driving for the passenger economy will pose. Intel, in working with Strategy Analytics, finds that the Passenger Economy may be worth $7 trillion by 2050. The largest factor holding this new business space back may very well be consumer acceptance.
The burden on semiconductor processors and supporting ICs will be driven part by data. Massive amounts of data will be driven by multiple sensors, “so that you, if you are riding in it, you trust that the vehicle knows what it’s doing…you want to know that it can handle snow and ice.” The sensors complement each other. “As we go through more and more testing, and there’s more of those vehicles out there, we are learning about the combinations, how much redundancy, things like that, that you actually need in the vehicle.” Emerging pedestrians, variable weather conditions, and myriad navigation issues from differing state regulations to undocumented construction and potholes also contribute to the need for data from differing variables aimed at every possibility.
Such enormous amounts of data come not only as technical data from sensors on the car and from infrastructure, but from crowd-sourced data as well as personal data for drivers and passengers. Crowd-sourced data might include reporting new obstacles or construction to be incorporated into the AV’s navigating knowledge. The autonomous learning cycle continues as cars upload data to the cloud, which shares and uses the data to train other vehicles on the new information. Personal data gathered from within the car includes information about the passengers which will be critical to the new passenger economy as AVs become the foundation for new markets for services formed for passengers within the vehicle. New applications like robo-taxis, managing fleets of delivery trucks, and crowd-sourcing data for navigation and finding parking are within reach.
Challenges translate to the semiconductor industry as we try and solve associated problems. How do we store and share the data? What do we do with the data, and what data is saved? Areas of focus in this developing economy will be the speed of critical information and processing workload. Security is also a critical part of the AV vision. Both privacy and overall resistance to cyberattacks are of genuine concern. “How do we keep it secure? How do we make sure that there’s not a way for cyberattacks once those vehicles are out there?” posed Winter. In short, how do we trust autonomous vehicles in every way?
As we get to thousands and millions of autonomous vehicles, we will also need to understand how many we want to manage at one time. At scale, we can share safety data, create standards, and even promote an industry platform. Winter acknowledged that the semiconductor industry is not new to challenges, but indicated that the landscape will change, “We think we know what the sensors are, we think we know that kind of data is generated, but we can’t imagine what we are going to know in two years based on the speed of acceleration that we have seen so far developing in this space.”
