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a perception module," says Mobileye's Dan Galves, a unit of Intel.
This enables the vehicle to react to shapes and textures around it,
including those of people, vehicles, obstructions, lane markings
and traffic light colors. But while cameras can detect both types
of information, radar and LiDAR recognize only shapes.
Galves says, "we use cameras as the primary source of information for perception, and then use LiDAR and radar as a redundancy for shape. For texture, we use a high-definition map for
redundancy." All combined, "you can build a very accurate model
of the environment around the vehicle," he says.
To date, Mobileye has integrated LiDAR in demonstration
vehicles exclusively, including one it displayed at CES 2018. But
Galves says next year a "household name" automaker will launch
the first production vehicle with a Mobileye LiDAR-based system for Level 3 autonomy.
More, because the driver is always in control of the vehicle
at Levels 1 and 2, "it limits the amount of redundancy [needed],"
he says. "We don't really believe that LiDAR is necessary for
anything below Level 3."
Despite the advances, it could be another five years before most
LiDAR companies are ready for the mass market, says Dr.
Christoph Schroeder, director of vehicle intelligence in the autonomous driving team at Mercedes-Benz Research & Development
North America (MBRDNA) in Sunnyvale, CA. Suppliers are challenged to economically produce the internal chips needed to
operate LiDARs, Schroeder says. A fully self-driving car requires
at least four LiDARs to see all 360 degrees, he says.
Car vision and perception has quickly advanced since the auto
industry first began working on self-driving cars 10 years ago.
With cameras, it's possible to distinguish pedestrians from one
another, and that's "a huge step forward," Schroeder says. Similar
LiDAR's Growth Potential
breakthroughs occurred with radars. Yet there's still room for
improvement with all three sensor types (camera, radar and
LiDAR) and the deep learning software that works with them.
MBRDNA and other automakers have dedicated teams working
on car perception technologies "to make it robust and able to
handle more situations," he says.
Daimler AG and MBRDNA are pursuing parallel paths,
Schroeder says. The first is evolutionary and leads to improved
ADAS on vehicles that are in or nearing production. The second
is revolutionary, leading towards fully self-driving cars. The flagship S-Class is an example of the former; a new generation introduced last year uses map and navigation data to enhance camera
and radar sensing to better automate driving behavior in curves.
Regarding the latter, Schroeder mentions MBRDNA's joint venture with Bosch, announced last year.
Toyota is opening an automated vehicle test facility in Ottawa
Lake, MI, in October. Under the auspices of the Toyota Research
Institute, the facility is designed to "safely replicate demanding
'edge case' driving scenarios, too dangerous to perform on public
roads." But its focus is on ADAS, not autonomy.
BMW opened a new Autonomous Driving Center in Munich,
Germany this year that houses 1,800 workers, including some
BMW partners such as Intel and Mobileye.
PUZZLE PIECES: MECHANICAL, SOLID STATE
There are basically two kinds of LiDAR available to automakers: solid-state, which contain no moving parts, and mechanical, which contain rotating mirrors. But a third type is also on
the market from one supplier - a solid-state "hybrid" LiDAR
that spins on a ball bearing.
Self-driving cars are expected to surge between now and the end of the next decade.
Number of Cars
Source: ABI Research
2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
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