google automatic driving vehicle

Google announced the company apart in the normal business operations, is also developing the technology allows automatic driving vehicle. The company said in a blog, using this technology can reduce by half the number of deaths due to traffic accidents worldwide each year about 60 million lives saved. At the same time Google also hopes to reduce carbon dioxide emissions.

Two recent announcements have made self-driving cars seem a lot closer to reality. The first comes from the Army, which is now using self-driving vehicles to guard a large military facility and nuclear waste dump in Nevada. And then there's Google, which recently announced that it has developed self-driving cars that have logged over 100,000 miles on real roads in real traffic.

What is going on inside these cars to make it possible for them to drive themselves? Let's take a look.

You could, in theory, turn any car into a self-driving car. The first thing you would have to do is make it possible for a computer to control the car. This is not quite as easy as it sounds, but it is relatively straightforward. The computer needs to be able to turn the steering wheel, push the accelerator and brake pedals, move the gear shift control and start the engine.

These tasks, at least in experimental self-driving cars, are often accomplished with motors. A motor is mounted so it can turn the existing steering wheel. Another motor is able to put pressure on the accelerator and brake pedals. And so on. It is not a particularly elegant solution, but it gets the job done. As production cars become more advanced, drive-by-wire systems are becoming more common. In cars with drive-by-wire, a computer can hook directly into the existing control systems.

The next thing that a self-driving car needs is sensors, and here things get pretty complicated today. A human being drives a car by using his or her eyes as the sole sensor. The human visual system is amazing in this regard, because it is able to accurately judge the presence of obstacles, their distance, their relative size based on distance, their speed, etc. A human being also recognizes what he is seeing. If a human being sees a fence, she can accurately predict with high certainty that it will not jump into the middle of the road. On the other hand, a child playing with a ball on a sidewalk is a different story.

Computer vision systems are nowhere near this point in their development. So they rely on extra sensors to provide more information. Self-driving cars do have camera-based vision systems that they use to see other cars, unexpected obstacles, road markings and signs. But in addition, self-driving cars almost always have GPS sensors so that they have a better idea of exactly where they are and where they are pointing. They also have LADAR systems — laser scanners that can look for nearby objects and accurately judge their distance. They may have RADAR systems as well. They may also have infrared sensors to improve night vision.

These sensors all feed into a powerful onboard computer (often multiple computers) that process all the data that the sensors are gathering. The internal computer will have access to a database of maps and other relevant information. For example, engineers may pre-drive a route and pre-catalog all signs, road markings, curbs, crosswalks, traffic lights, etc. that the self-driving car will encounter along the road. This way, the car knows what to expect and can plan accordingly. Finally, the onboard computer may also be communicating by radio with bigger computers holding even more data.