Self-Driving Car technology that is useful or risk!?

There is one word to say that "When it comes to self-driving cars, the future was supposed to be now." It has been true when there are the Motors-Mobile Powerhouses as General Motors, Google’s Waymo, Toyota, and Honda which they can make "it" in 2020. On the other hand, it has been not ready for this year. Why!? Here are four questions you might have had about this long-promised technology, and why the future we were promised still hasn’t arrived. In simple words, it has more risks than useful. Let's see the details!!

Good for the environment with the self-driving car?

There are many arguments about it are good for the environment!? Most of all can reduce more car trips and traffic jams by making car ownership unnecessary and transitioning society to a model where most people don’t own a car and just call for one when they need one. On the other hand, they aren't different from many cars that have a driver to drive, for they have controlled by people too. And they make "more air-pollution" and "more fuel efficiency".

There is one study attempting to estimate the effects of self-driving cars on car use behavior simulated a family having a self-driving car by paying for them to have a chauffeur for a week and telling them to treat the chauffeur service the way they’d treat having a car that could drive it. The result is there were many car trips. So the researchers will research more time for sure to be useful in the future.

When will we get a self-driving car?

It's a simple word to think. But it is exasperatingly difficult to get a good estimate of how long until self-driving cars happen for the people around the World? Because of many automobile powerhouses guarantee that it has a problem about "the software" for the self-driving car. Moreover, they can't guarantee them that they can work in the long period.

How can we guarantee for its safety and work?

There was the first time a self-driving car ran down a pedestrian. An Uber car with a safety driver behind the wheel hit and killed Elaine Herzberg, a 49-year-old woman walking with her bicycle across the street in Tempe, Arizona in March 2018.

The incident was a reminder that its technology still had a long way to go. Some people were quick to point out that humans frequently kill other humans while driving, and that even if self-driving cars are much safer than humans, there will be some fatal incidents with self-driving cars. That’s true as far as it goes. But it misses a key point. Human driving produces one fatal accident every 100 million miles driven.

Waymo, the leader in miles driven, just reached 20 million miles driven. It hasn’t had a fatal accident yet, but given the number of miles its cars have driven, it’s simply far too soon to prove that they’re as safe as or safer than a human driver.

The Limitations for a self-driving car?

The limitations are even with extraordinary amounts of time, money, and effort invested, no team could figure out how to have AI solve a real-world problem: navigating our roads with the high degree of reliability needed.

The problem is the need for lots of training data. The ideal way to train a self-driving car would be to show it billions of hours of footage of real driving and use that to teach the computer good driving behavior. Modern machine learning systems do really well when they have abundant data, and very poorly when they have only a little bit of it. But collecting data for self-driving cars is expensive. And since some events are rare — witnessing a car accident ahead, say, or encountering debris on the road — it’s possible for the car to be out of its depth because it has encountered a situation so infrequently in its training data.

Carmakers have tried to get around this in lots of ways. They’ve driven more miles. They’ve trained the cars in simulations. They sometimes engineer specific situations so that they can get more training data about those situations for cars. But it’s a hard problem, and progress has been slow.