IN FUTURE WITHOUT DRIVERS,DO
CARS EXIST
Carmakers are developing vehicles that have an
increasing ability to autonomously drive themselves, potentially reducing
accidents and traffic congestion.
A
silver BMW 5 Series is weaving through traffic at roughly 120 kilometers per
hour (75 mph) on a freeway that cuts northeast through Bavaria between Munich
and Ingolstadt. I’m in the driver’s seat, watching cars and trucks pass by, but I haven’t touched the steering wheel, the
brake, or the gas pedal for at least 10 minutes. The BMW approaches a truck
that is moving slowly. To maintain our speed, the car activates its turn signal
and begins steering to the left, toward the passing lane. Just as it does,
another car swerves into the passing lane from several cars behind. The BMW
quickly switches off its signal and pulls back to the center of the lane,
waiting for the speeding car to pass before trying again.
Putting your life in
the hands of a robot chauffeur offers an unnerving glimpse into how driving is
about to be upended. The automobile, which has followed a path of steady but
slow technological evolution for the past 130 years, is on course to change
dramatically in the next few years, in ways that could have radical economic,
environmental, and social impacts.
The first autonomous systems, which are able to control steering,
braking, and accelerating, are already starting to appear in cars; these
systems require drivers to keep an eye on the road and hands on the wheel.
But the next generation, such as BMW’s self-driving prototype,
could be available in less than a decade and free drivers to work, text, or
just relax. Ford, GM, Toyota, Nissan,
Volvo, and Audi have all shown off cars that can drive themselves, and they
have all declared that within a decade they plan to sell some form of advanced
automation—cars able to take over driving on highways or to park themselves in
a garage. Google, meanwhile, is investing millions in autonomous driving software, and its driverless cars have become a
familiar sight on the highways around Silicon Valley over the last several
years.
The allure of automation for car companies is huge. In a fiercely
competitive market, in which the makers of luxury cars race to indulge
customers with the latest technology.
Thanks to autonomous driving, the road ahead seems likely to have
fewer traffic accidents and less congestion and pollution. Data published last
year by the Insurance Institute for Highway Safety, a U.S. nonprofit funded by
the auto industry, suggests that partly autonomous features are already helping
to reduce crashes. Its figures, collected from U.S. auto insurers, show that
cars with forward collision warning systems, which either warn the driver about
an impending crash or apply the brakes automatically, are involved in far fewer
crashes than cars without them.
More comprehensive autonomy could reduce traffic accidents further still. The National Highway Traffic Safety Administration estimates that more than 90 percent of road crashes involve human error, a figure that has led some experts to predict that autonomous driving will reduce the number of accidents on the road by a similar percentage. Assuming the technology becomes ubiquitous and does have such an effect, the benefits to society will be huge. Almost 33,000 people die on the roads in the United States each year, at a cost of $300 billion, according to the American Automobile Association. The World Health Organization estimates that worldwide over 1.2 million people die on roads every year.
Meanwhile, demonstrations conducted at the University of
California, Riverside, in 1997 and experiments involving modified road vehicles
conducted by Volvo and others in 2011 suggest that having vehicles travel in
high-speed automated “platoons,” thereby reducing aerodynamic drag, could lower
fuel consumption by 20 percent. And an engineering study published last year
concluded that automation could theoretically allow nearly four times as many
cars to travel on a given stretch of highway. That could save some of the 5.5
billion hours and 2.9 billion gallons of fuel that the Texas Transportation
Institute says are wasted by traffic congestion each year.
If all else fails, there is a big
red button on the dashboard that cuts power to all the car’s computers. I
practiced hitting it a few times.
But such projections tend to overlook just how challenging it will
be to make a driverless car. If autonomous driving is to change transportation
dramatically, it needs to be both widespread and flawless. Turning such a
complex technology into a commercial product is unlikely to be simple. It could
take decades for the technology to come down in cost, and it might take even
longer for it to work safely enough that we trust fully automated vehicles to
drive us around.
German engineering
Much of the hype about autonomous driving has, unsurprisingly, focused on Google’s self-driving project. The cars are impressive, and the company has no doubt insinuated the possibility of driverless vehicles into the imaginations of many. But for all its expertise in developing search technology and software, Google has zero experience building cars. To understand how autonomous driving is more likely to emerge, it is more instructive to see what some of the world’s most advanced automakers are working on. And few places in the world can rival the automotive expertise of Germany, where BMW, Audi, Mercedes-Benz, and Volkswagen are all busy trying to change autonomous driving from a research effort into a viable option on their newest models.
Much of the hype about autonomous driving has, unsurprisingly, focused on Google’s self-driving project. The cars are impressive, and the company has no doubt insinuated the possibility of driverless vehicles into the imaginations of many. But for all its expertise in developing search technology and software, Google has zero experience building cars. To understand how autonomous driving is more likely to emerge, it is more instructive to see what some of the world’s most advanced automakers are working on. And few places in the world can rival the automotive expertise of Germany, where BMW, Audi, Mercedes-Benz, and Volkswagen are all busy trying to change autonomous driving from a research effort into a viable option on their newest models.
Shortly after arriving in Munich, I found myself at a test track
north of the city getting safety instruction from Michael Aeberhard, a BMW
research engineer. As I drove a prototype BMW 5 Series along an empty stretch
of track, Aeberhard told me to take my hands off the wheel and then issued
commands that made the car go berserk and steer wildly off course. Each time, I
had to grab the wheel as quickly as I could to override the behavior. The
system is designed to defer to a human driver, giving up control whenever he or
she moves the wheel or presses a pedal. And if all else fails, there is a big
red button on the dashboard that cuts power to all the car’s computers. I
practiced hitting it a few times, and discovered how hard it was to control the
car without even the power-assisted steering. The idea of the exercise was to
prepare me for potential glitches during the actual test drive. “It’s still a
prototype,” Aeberhard reminded me several times.
Nico Kämpchen, a project manager at BMW, tests the company’s
highly automated driving technology on the autobahn.
The car looked normal from the outside. There’s no place on a
sleek luxury sedan for the huge rotating laser scanners seen on the prototypes
being tested by Google. So BMW and other carmakers have had to find ways to
pack smaller, more limited sensors into the body of a car without compromising
weight or styling.
Concealed inside the
BMW’s front and rear bumpers, two laser scanners and three radar sensors sweep
the road before and behind for anything within about 200 meters. Embedded at
the top of the windshield and rear window are cameras that track the road
markings and detect road signs. Near each side mirror are wide-angle laser
scanners, each with almost 180 degrees of vision, that watch the road left and
right. Four ultrasonic sensors above the wheels monitor the area close to the
car. Finally, a differential Global Positioning System receiver, which combines
signals from ground-based stations with those from satellites, knows where the
car is, to within a few centimeters of the closest lane marking.
Several computers inside the car’s trunk perform split-second
measurements and calculations, processing data pouring in from the sensors.
Software assigns a value to each lane of the road based on the car’s speed and
the behavior of nearby vehicles. Using a probabilistic technique that helps
cancel out inaccuracies in sensor readings, this software decides whether to
switch to another lane, to attempt to pass the car ahead, or to get out of the
way of a vehicle approaching from behind. Commands are relayed to a separate
computer that controls acceleration, braking, and steering. Yet another
computer system monitors the behavior of everything involved with autonomous
driving for signs of malfunction.
Impressive though BMW’s autonomous highway driving is, it is still
years away from market. To see the most advanced autonomy now available, a day
later I took the train from Munich to Stuttgart to visit another German
automotive giant, Daimler, which owns Mercedes-Benz. At the company’s research
and development facility southeast of the city, where experimental new models
cruise around covered in black material to hide new designs and features from
photographers, I got to ride in probably the most autonomous road car on the
market today: the 2014 Mercedes S-Class.
A jovial safety engineer drove me around a test track, showing how
the car can lock onto a vehicle in front and follow it along the road at a safe
distance. To follow at a constant distance, the car’s computers take over not
only braking and accelerating, as with conventional adaptive cruise control,
but steering too.
Using a stereo camera,
radar, and an infrared camera, the S-Class can also spot objects on the road
ahead and take control of the brakes to prevent an accident. The engineer eagerly demonstrated this by
accelerating toward a dummy placed in the center of the track. At about 80
kilometers per hour, he took his hands off the wheel and removed his foot from
the accelerator. Just when impact seemed all but inevitable, the car performed
a near-perfect emergency stop, wrenching us forward in our seats but bringing
itself to rest about a foot in front of the dummy, which bore an appropriately
terrified expression.
With such technology already on the road and prototypes like BMW’s in the works, it’s tempting to imagine that total automation can’t be far away. In reality, making the leap from the kind of autonomy in the Mercedes-Benz S-Class to the kind in BMW’s prototype will take time, and the dream of total automation could prove surprisingly elusive.
For one thing, many of the sensors and computers found in BMW’s
car, and in other prototypes, are too expensive to be deployed widely. And
achieving even more complete automation will probably mean using more advanced,
more expensive sensors and computers. The spinning
laser instrument, or LIDAR, seen on the roof of Google’s cars, for
instance, provides the best 3-D image of the surrounding world, accurate down
to two centimeters, but sells for around $80,000. Such instruments will also
need to be miniaturized and redesigned, adding more cost, since few car
designers would slap the existing ones on top of a sleek new model.
Cost will be just one factor, though. While several U.S. states
have passed laws permitting autonomous cars to be tested on their roads, the
National Highway Traffic Safety Administration has yet to devise regulations
for testing and certifying the safety and reliability of autonomous features.
Two major international treaties, the Vienna Convention on Road Traffic and the
Geneva Convention on Road Traffic, may need to be changed for the cars to be
used in Europe and the United States, as both documents state that a driver
must be in full control of a vehicle at all times.
The image above shows 3-D data captured by the LIDAR instrument
atop a Google self-driving car, where color indicates height from the ground.
Inset is the view from the car’s front-facing
camera.
An important challenge with a system that drives all by itself,
but only some of the time, is that it must be able to predict when it may be
about to fail, to give the driver enough time to take over. This ability is
limited by the range of a car’s sensors and by the inherent difficulty of
predicting the outcome of a complex situation. “Maybe the driver is completely
distracted,” Werner Huber said. “He takes five, six, seven seconds to come back
to the driving task—that means the car has to know [in advance] when its
limitation is reached. The challenge is very big.”
Before traveling to Germany, I visited John Leonard, an MIT
professor who works on robot navigation, to find out more about the limits of
vehicle automation. Leonard led one of the teams involved in the DARPA Urban
Challenge, an event in 2007 that saw autonomous vehicles race across mocked-up
city streets, complete with stop-sign intersections and moving traffic. The
challenge inspired new research and new interest in autonomous driving, but Leonard
is restrained in his enthusiasm for the commercial trajectory that autonomous
driving has taken since then. “Some of these fundamental questions, about
representing the world and being able to predict what might happen—we might
still be decades behind humans with our machine technology,” he told me. “There
are major, unsolved, difficult issues here. We have to be careful that we don’t
overhype how well it works.”
Leonard suggested that much of the technology that has helped
autonomous cars deal with complex urban environments in research projects—some
of which is used in Google’s cars today—may never be cheap or compact enough to
be employed in commercially available vehicles. This includes not just the LIDAR but also an inertial navigation system, which provides precise positioning
information by monitoring the vehicle’s own movement and combining the
resulting data with differential GPS and a highly accurate digital map. What’s
more, poor weather can significantly degrade the reliability of sensors, Leonard
said, and it may not always be feasible to rely heavily on a digital map, as so
many prototype systems do. “If the system relies on a very accurate prior map,
then it has to be robust to the situation of that map being wrong, and the work
of keeping those maps up to date shouldn’t be underestimated,”
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