Autonomous Vehicle Engineering - September 2021 - 11

Sensors
Processing capability TOPs-out
Sensors are the vehicle's eyes and ears, but
their inputs must be analyzed, processed and
acted upon. A hefty amount of computing
power is needed to fuse complex data from
several sensors and determine how those
inputs should be used.
Many, but not all, sensor modules possess
little intelligence, feeding information to zonal
processing modules that do a bit of processing
before the data goes to a centralized
controller. These powerful central controllers
fuse data from cameras, radar and lidar, then
decide how to assist the driver - or automatically
brake, steer or accelerate. Meanwhile,
Tier 1 suppliers are taking advantage of rapid
increases in processing power.
" We've gone from 30 TOPS (trillion
operations per second) to 1,000 TOPS in four
to five years, " said Andy Whydell, VP of systems
product planning for ZF. " The industry
is ramping up processing to handle all the
inputs, but that needs to be balanced with
power consumption. "
The performance gains in processors can
be combined with sensors that also are leveraging
semiconductor production advances.
Design teams are using multiple sensor types
to blend the strengths of different technologies,
then they're exploiting powerful
controllers to run multiple analysis tools. It's
a potent combination.
" By putting cameras and radar together
to check each other, it's amazing what the
processors can do with the extra information,
especially if you have enough processing
power to run different algorithms in parallel, "
said Martin Duncan, ADAS division general
manager at STMicroelectronics.
Stripping intelligence from sensors generates
significant benefits. Sensor counts are
rising, with plans for 30 or so on a highly automated
vehicle. Eliminating power demand
and shrinking size are important factors for
hiding sensors.
" Removing some processing power means
sensors are smaller and power consumption
is less, " Whydell said. " Smaller packages
make it easier to integrate sensors into lighting
structures or the A- and B-pillars. "
However, some sensor modules will
include an integrated microprocessor. This
" distributed processing " model reduces
bandwidth requirements while also reducing
the workload of the vehicle's central controller.
Some lidar packages include processors
Lidar sensors will include
some processing capabilities.
to analyze light that bounces back to the
sensor, sending the main controller more
pertinent data.
" We look to subsume more functions,
doing some first-level computing, " said
Anand Gopalan, Velodyne's CEO. " The camera
guys talk about using GPUs (graphics
processing units), lidar does more at the
'edge,' so systems can get away with using
low-cost FPGAs (field programmable gate
arrays) or low-cost CPUs. "
Artificial intelligence will play a role when
processors analyze sensor inputs; AI takes
a fair amount of computing power, but its
benefits far outweigh the processing demand.
Determining what's being seen by an
array of sensors can be a confusing task for
machines that only know what's been written
into software.
" AI can help cameras deal with something
Processing power has leapt 30 fold in the
past five years.
seeing five radar sensors being required to achieve the
ADAS functions - two in the rear corner, two in the
front corner and one in the front, " said Prajakta Desai,
marketing manager for Texas Instruments mmWave
automotive radar. " For Level 3, additional sensors on
the side would be needed for 360-degree coverage.
For Level 4 and beyond, we believe that all the sensing
modalities (vision, radar and lidar) might be required
to achieve fully autonomous driving. "
they're not trained to recognize, " Whydell
said. " A European OEM [during on-road
testing] came across a kangaroo that was
sometimes on the ground, sometimes in the
air, so the system couldn't tell whether it was
a bird or not. "
Ryan Gehm
Sensors galore
Most front-facing sensing systems rely on a combination
of sensor types. Though it's possible to provide
full autonomy with a single technology, combining
cameras, radar and lidar provides some redundancy
while also adding complimentary sensing capabilities.
" None of the available sensor technologies - be
it camera, lidar, radar or ultrasonic - will be able to
realize automated driving functionalities on their own, "
AUTONOMOUS VEHICLE ENGINEERING
September 2021 11
ZF
Velodyne

Autonomous Vehicle Engineering - September 2021

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