Google's self-driving cars program, Waymo, has recorded the most successful run in the autonomous vehicles category, until now. More is expected in the AV domain in the coming years, something to wait and watch out for.

With continual advancements in artificial intelligence, it won't be long before machine learning touches more and more aspects of our lives – including the way we drive. As more autonomous cars hit the road, the way we can expect to drive in the future is shifting. In this course, you'll learn the robotics fundamentals and machine learning concepts that go into self-driving cars. The course will help you develop an understanding of artificial neural networks, and some of the complex algorithms that are applied in these vehicles. Increase your knowledge about machine learning with The Robotics & Machine Learning of Self-Driving Cars.

Here's why: Google has created a virtual track out of Mountain View. The key to Google's success has been that these cars aren't forced to process an entire scene from scratch. Instead, their teams travel and map each road that the car will travel. And these are not any old maps. They are not even the rich, road-logic-filled maps of consumer-grade Google Maps.

Once a secret project, Google's self-driving cars are now out in the open, quite literally, with the company test-driving them on public roads and, on one occasion, even inviting people to ride inside one of the robot vehicles as it raced around a closed course. Google's fleet of robotic Toyota Priuses has now logged more than 190,000 miles (about 300,000 kilometers), driving in city traffic, busy highways, and mountainous roads with only occasional human intervention. The project is still far from becoming commercially viable, but Google has set up a demonstration system on its campus, using driverless golf carts, which points to how the technology could change transportation even in the near future. Stanford University professor Sebastian Thrun, who guides the project, and Google engineer Chris Urmson discussed these and other details in a keynote at the IEEE International Conference on Intelligent Robots and Systems in San Francisco last month. Thrun and Urmson explained how the self-driving car works and showed videos of the road tests, including footage of what the on-board computer "sees" [image below] and how it detects other vehicles, pedestrians, and traffic lights.

Being able to commute back and forth to work while sleeping, eating, playing Trivia Crack or catching up on your favorite blogs in Feedly is a concept that is equally appealing and seemingly far-off and too futuristic to actually happen. When Google announced their autonomous car project in 2008, visions of Minority Report began to swirl in our heads while we wondered about the possibilities of a car that really had no need for us to do anything other than turn it on. This same car wouldn't have to worry about accidents, distraction, or driving under the influence while it made thousands – or even millions – of split-second calculations in order to keep your safe. You see, as it turns out, humans are remarkably bad at driving. "People are not great at driving -- 30,000 people die in car accidents each year (in the United States). Machines can be much better than humans when it comes to driving; they don't drink or text and can think faster."