Over one million people lose their lives in automobile accidents each year.
Researchers are trying to reduce accidents and save lives by developing technologies
that assist people with driving cars, and will eventually allow cars to drive themselves!
Self-driving cars may sound like science fiction, but experimentation with automated driving
systems began back in the 1920s.
Beginning with remote controlled “phantom autos” from 100 years ago, automated driving
systems today are computer-controlled, and they work by creating a map of their surroundings
using sensors.
Driverless cars have an exciting potential to revolutionize the way we travel, though
there is still a long road ahead.
The Society of Automotive Engineers has a six-level classification system to define
the different levels of driving automation along a spectrum.
The classification ranges from level 0, or no automation, to level 5, or complete automation.
The higher the level, the less input is required from the human driver to operate the car.
At the moment, the highest automation level available for consumer purchase is somewhere
between levels 2 and 3, which means that today’s semi-autonomous cars can steer, accelerate,
and/or decelerate on their own, but the driver must intervene if certain conditions make
it so that the car can’t interpret its surroundings.
Automobile and tech companies are experimenting with higher levels of automation, but completely
automated cars will likely not be available for another few decades.
One important technology that allows today’s semi-autonomous vehicles to “see” is LIDAR,
short for “light detection and ranging.”
LIDAR sensors determine distances between the car and surrounding objects -- like other
cars, pedestrians, bicyclists, and even curbs -- by sending out pulses of light and measuring
how long it takes for the light to reflect back to the sensor.
But LIDAR can only sense objects that are relatively close to the car, and sometimes
its measurements are not accurate enough to distinguish one object from another.
And when multiple self-driving cars are on the same road, their LIDAR signals can interfere.
Cameras are another critical technology that help vehicles interpret the road: they visually
detect objects like traffic lights, street signs, and road markings.
Other technologies such as GPS, radar, and vehicle-to-vehicle communication allow cars
to understand their precise position on the road relative to nearby objects.
The power of driverless cars lies in their dependence on multiple sensors; each one provides
specialized information on what’s happening on the road, and they support each other in
case one fails.
Once the car’s sensors collect all this information, computers analyze it and decide
how the car should drive in response to its surroundings.
Processing such a large amount of data is a challenge, and there’s no way to program
a computer to respond to every possible signal it might receive.
For that reason, researchers are experimenting with machine learning, which trains a car’s
computer on large amounts of sample data so that it can eventually make decisions on data
it has never seen.
Despite their supply of high-tech sensors, self-driving cars can fall short.
For instance, automated driving systems don’t function as well when there is heavy precipitation,
when lane divisions are not clearly painted, or when litter clutters the road, since their
sensors can get “confused.”
In addition, imagine a pedestrian crossing the street: a driver sees the pedestrian,
makes eye contact, and waves them on, signaling that the driver will stop their car so the
pedestrian can cross safely.
But autonomous vehicles cannot make eye contact with human beings, or communicate in such
subtle ways.
There are also questions of ethics regarding driverless cars.
Who is responsible when an autonomous vehicle gets into a car accident?
With no driver to blame, is it the fault of the car manufacturer?
The people who developed the computer programs?
Or the local authorities responsible for regulations, road design, and maintenance?
Another ethical dilemma is concern for driver privacy.
For example, some of today’s semi-autonomous vehicles have driver-assist technologies such
as eye trackers, which monitor a driver’s attention using a camera that detects head
position, eye position and eyelid movement.
In some semi-autonomous vehicles, if the system determines that the driver is distracted or
asleep, the car will alert the driver, or, if necessary, slow itself to a stop.
While there are many challenges to overcome, autonomous vehicles offer a promising future.
Unlike humans, they can’t become tired or inebriated.
Car travel could become more accessible, if it is easier for people with physical disabilities
to operate a driverless vehicle.
On the other hand, the financial accessibility of driverless cars is variable: currently,
cars with automated driving systems range in price from 15-100,000 USD.
Self driving cars could also make roads safer and more efficient to travel on, once their
sensor technology has advanced to the point where they can interpret and respond to a
variety of road conditions better than human drivers.
This increased efficiency, combined with cars being powered by electricity, means self-driving
cars could play a major role in reducing the environmental impact of the transportation
sector.
Although we are still at least a few decades away from commercially available, fully autonomous
vehicles that were first dreamed of a century ago, there’s no doubt that we’ve begun
paving the way towards a driverless future.