Data flow issues may slow down robo-car emergence
MADISON, Wis. – Car companies rarely discuss behind-the-scene development work on their autonomous vehicles.
The notable exception to this rule is CPU giant Intel, which styles itself as a “data company” and sees the challenges of autonomous driving as problems of data flow.
In developing highly automated vehicles, Intel focuses on overseeing and analyzing how data -- once captured by test vehicles -- is ingested, sorted out, learned and simulated at data centers. Intel hopes that this sort of granular knowledge will help determine how best to process data inside a cars.
EE Times recently interviewed Jack Weast, Intel’s chief architect of Autonomous Driving Solutions. We discussed the exploding volume of data collected by autonomous cars, and how the data glut is actually being processed – at data centers and inside vehicles.
Recently, Intel has been warning about “the coming flood of data in autonomous vehicles.” It estimates that an autonomous car could generate as much as 4 terabytes per 1.5 hours on the road.
So, is Intel saying that every autonomous car roboting around in 2021 will be collecting, storing and uploading that much data?
Not quite. “Let us first explain autonomous vehicle data processing by separating what’s happening during development phase from deployment,” said Weast.
Intel clarified that four terabytes per 1.5 hours is an estimate of how much data a training test vehicle would collect during the development phase of autonomous driving.
Assuming the test vehicle drives four to five hours per day, it will end up collecting “tens of terabytes of data,” said Weast, “which is stored in a hard disk drive inside the test vehicle.”
At this point, no filters or processing are applied to collected data. Everything captured is stored in HDD for later analysis.
Certainly data in terabyte chunks is too huge for wireless transmission to a data center. Instead, “We would physically take the HDD out of a vehicle and bring it over to a data center,” Weast.
Data center architecture matters
Once at the data center, the next step is important, he noted, “Because this is where the data center architecture matters.”
There are five different processing stages at a data center, according to Weast.
Continue to page two on Embedded's sister site, EE Times: "Intel sees robo-car as data flow issue."