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 The company at the forefront of the race, Google Inc, is creating
intricate maps that detail every tree and curb along the road - an
expensive endeavor that other companies could find difficult to
match.
Newer entrants such as ride-share service Uber and Apple Inc could
take a shortcut and develop a car capable of piloting itself without
such elaborate and expensive blueprints, industry experts say.
The dueling technological approaches represent more than a
philosophical divide: they hint at how and when the companies,
competing to expand into a significant new class of product, could
put autonomous cars onto the road.
Raj Rajkumar, one of the leading experts on self-driving cars at
Carnegie Mellon University, said the map-based approach makes sense
for a company with Google’s resources but is not required.
“Google is capable of collecting all this information. In our case,
we don’t have that capability, so we have to be creative. It turns
out that’s sufficient” said Rajkumar, who has developed a modified
Cadillac that relies on radars, video cameras and six laser scanners
and in 2013 drove 33 miles (53 km) to the local airport without
human intervention or 3D maps.
Both approaches currently have limitations, and even the most
optimistic acknowledge that a variety of technological, regulatory
and legal issues mean it will be years, perhaps longer, before
completely self-driving cars hit the road.
Apple is studying the potential for a self-driving car, a source
familiar with the matter has told Reuters. Uber, which operates the
popular ride-hailing service, announced a partnership with Carnegie
Mellon University in January to focus on self-driving cars. Electric
car maker Tesla Motors Inc is developing self-driving technology,
and traditional automakers including General Motors Co and Nissan
Motor Co Ltd are also adding automated features into their vehicles.
And companies such as Nokia's Here are also developing detailed 3D
maps that potentially could be licensed by car companies.
Apple, Uber and Google declined to discuss self-driving cars.
MAPS OF THE FUTURE
Mapping the entire United States to the level of detail used by
Google’s cars could easily cost hundreds of millions of dollars and
take five to seven years, said Egil Juliussen, an analyst with
research firm IHS Automotive.
All autonomous cars rely on basic electronic maps for navigation and
lane centering. But Google’s cars use far more detailed 3D maps,
which the company creates by using laser scanners. Google analyzes
the data, determining where traffic lights and stop signs are, for
instance, so that the vehicle "knows" exactly where it is.
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Google’s pod-shaped prototype cars use on-board sensors, including
the distinctive spinning laser on the car’s roof, to detect anything
not on the map, such as vehicles or baby carriages.
Google’s existing mapping know-how and resources give it an extra
advantage, said Boris Sofman, the co-founder and CEO of Anki, a
robotics company that makes self-driving toy cars.
But the maps can quickly become stale, he said. Fresh snow could
change the landscape.
“The map-based approach allows you to drive accurately in a
controlled environment, where you know that things don’t change
much,” said Dirk Langer, the chief technology officer of ASCar,
which makes sensors for autonomous vehicles.
Gated retirement communities and college campuses would be examples,
he said, arguing that for broader uses sensors are more important
than 3D maps. Cars might be able to pilot themselves without using
3D maps in specially designated lanes on streets and highways, said
John Absmeier, the global business director of autonomous driving
for auto supplier Delphi Automotive Plc.
But advances in sensor technology are also needed for cars to truly
become autonomous. Carnegie Mellon's Cadillac required some sensors
mounted on street lights to make its 2013 journey to the airport.
“We think we can handle 90 percent of road cases," said Carnegie
Mellon's Rajkumar, "but getting to 100 percent will take longer.”
(Reporting by Alexei Oreskovic; Editing by Peter Henderson, Sue
Horton and Lisa Shumaker)
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