Autonomous Vehicle Engineering - November 2021 - 19

Emerging Technologies
Autonomy's
Computing Edge
by Paul Seredynski
Reducing latency by processing data closer to the devices
using it will play a huge role in AV functional safety. Stellantis is
a first mover in edge-computing trials.
Computing clouds get more headlines, but edge
computing is likely to play a more crucial second-tosecond
role in the autonomous-vehicle (AV) future.
Roughly defined as bringing the processing of data
physically closer to the devices requiring it, edge
computing will form a critical part of the digital infrastructure
required to make AVs a safe and responsive
transportation option. If computing clouds are the
centralized processing centers forming the hub of a
network wheel, then edge computing exists out towards
the end of the wheel's spokes, closer to where data is
acted on or being gathered.
Digital networks can transfer data at the speed
of light, which sounds fast until a split-second traffic
decision is required - and the cloud-based server
feeding data to your AV is half a world away. Latencies
measured in microseconds might not dampen a
web-browsing experience, but not knowing that the
bridge you're about to cross just iced over, or another
vehicle just pulled out to block the intersection you're
entering could prove genuinely detrimental. Edge
computing seeks to leverage locality to improve the
relevancy and immediacy of vital data.
Out of the cloud
Edge computing is a natural extension of cloud
computing, which seeks to offload sometimes
massive processing requirements from a device (i.e.,
AUTONOMOUS VEHICLE ENGINEERING
a smartphone, or a vehicle) to scalable servers, which
can take up entire city blocks and be located thousands
of miles from the device using the data. Cloud
architectures permit access to enormous computing
resources, with the only real downside being latency.
" If you think about the difference in latency of
going to the corner store versus going across town to
the big Costco, you have a shorter trip. You have it right
there where it's much faster, " explained Josh Johnson,
an enterprise architect with Akamai Technologies,
an edge-computing concern and provider of one of
the world's largest distributed-computing platforms.
" And the same thing with the data. It's much lower
latency when you have the data and processing close
to where the user is, as opposed to going halfway
across the country to get to an on-premise data center
or a cloud region. "
Johnson, who has prior experience with automotive
OEMs, noted that latency is typically measured
in thousandths of a second, but that's still a crucial
interval. " If you look at trying to set up a central
location, the speed of light sounds quick, but then
you look across continents and that can easily be 200
milliseconds, " he said. " Doesn't sound like a lot, but
when you have a lot of that going back and forth at a
time, it all adds up, and a lot of decisions need to be
made quicker than that. "
Edge computing eliminates expansive data travel
November 2021 19
Autonomous Vehicle Engineering - November 2021

Table of Contents for the Digital Edition of Autonomous Vehicle Engineering - November 2021
