Truck & Off-Highway Engineering - October 2018 - 24

Sensing changes in
autonomous trucks

AUTOMATED TECHNOLOGY FEATURE

Off-highway environments are simple-but not
It is the best of environments and the worst of environments for designers
of autonomous off-highway vehicles. Freight haulers and some agricultural
equipment are in some ways easier to automate than passenger cars, but
many construction machines pose extremely vexing challenges.
Mining companies have been using autonomous trucks for a few years,
with a number of users saying efficiency gains average 15-20% over conventional trucks. In many ways, hauling freight from mines to ports or rail depots is far simpler than autonomously driving trucks on highways.
"The mine might be 20 miles from the rail head," said Dan Williams,
ADAS and Autonomy Director at ZF Commercial Vehicle Technologies. "The
driving path is very predictable-they run the same route every day, often in
a remote environment where there aren't a lot of intersections and they
don't have to deal with many drivers or pedestrians."
Passenger cars usually drive forward from point to point, so most of
their sensors face forward, with comparatively few facing rearward. But any
construction vehicle equipped with a backup alarm requires extensive sensing technologies on the front and back to provide autonomy.

Radars from
suppliers
like ZF
will be a
mainstay
of sensor
arrays that
include
cameras and
lidar.

The Danfoss
Autonomous Vehicle
Integration System
provides a platform for
combining sensors that
will help the vehicle
perform a range of
off-highway tasks.

Terry Costlow

24 October 2018

Redundancy is needed to ensure that a tractor's sensors don't
miss vehicles that impact the truck's ability to switch lanes.
environments are more controlled, vehicles are not exposed to the general public," Williams said. "One great
advantage is that you can put instrumentation in the
freight yard so the back of every trailer doesn't have to
be covered with sensors that cost more than the trailer
and its freight."
Remote controls are another way to gain the benefits of autonomy without making the investment
needed for fully autonomous vehicles. In environments
like mining and agriculture, a single remote operator
can monitor a few semi-autonomous vehicles, taking
control mainly when systems aren't able to make a
decision based on the sensor input. This technology
may help companies take steps towards autonomy
while developers are working to bring driverless vehicles to mainstream applications.
"We see remote control systems as an important
piece on the path to full autonomy and will play a critical
role in developing an overall machine control package,"
Woodard said. "In the future, I can see this technology
evolving to more 'tele-operation' applications, where
operators can control machines through a long-range
radio link or over an internet connection."
TRUCK & OFF-HIGHWAY ENGINEERING

CLOCKWISE FROM TOP RIGHT: ZF; DAIMLER; DANFOSS

"While off-highway machines are trying to get from one spot to another,
they're also performing work functions," said Chris Woodard, Business
Development Manager for Autonomous Machines, Danfoss Power Solutions.
"You may have a wheel loader that's transporting material or an excavator
that's digging. Or, all the work may be happening behind the machine, like
planting or tilling. These all require different sensor systems and configurations. In short, the flexibility and adaptability of autonomous systems for the
off-highway market is much higher than in the automotive industry."
Another difference is that while off-highway vehicles may need more sensors, they may not need the high resolutions used for autos. For many tasks in
construction and agriculture, distances are only a few meters and fewer objects
are important, so the high-resolution cameras used in cars aren't necessary.
"We've worked with lower-resolution cameras as well as different filtering technologies-infrared, for example-to pick out important pieces of
data, as well as high-resolution cameras that can pick out the finer details of
objects" Woodard said. "The trade-off is processing requirements, which
impacts the processor cost."
"We're working with different types of cameras and backend processing
for different tasks, so there isn't a 'one size fits all' solution. The type of application can determine which configuration works best. For example, a
lower-resolution camera is used for sprayers or mechanical weed removal to
differentiate between a plant or a weed simply based on the area it takes
up," he added.
However, Woodard noted that as automotive volumes for high-resolution cameras rise, it's likely that prices will fall to levels that make high-resolution cameras viable for off-highway systems. That will increase computing
requirements, but processor prices are also likely to decline over time.

Truck & Off-Highway Engineering - October 2018

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