From the excerpt “The more data it deals with in its deep le...

  As technology advances, the car industry has developed new ways to improve user experience. One of these ways includes using artificial intelligence to make cars self-driving. A self-driving car (also known as an autonomous car or driverless car) is a vehicle that uses a different number of sensors, radars, cameras, and artificial intelligence to travel to destinations without needing a human driver. Many companies have already started to manufacture self-driving cars, which are put through many tests to ensure they are eligible to be on the road without making any errors. To qualify as fully autonomous, a car must navigate routes to predetermined destinations without any human intervention.

  Artificial intelligence powers self-driving vehicle frameworks. Self-driving vehicle engineers utilize a great deal of information from image recognition systems, AI and neural networks to assemble frameworks that can drive self-sufficiently. The neural networks distinguish patterns in the data, which is fed to the AI calculations. That data include images from cameras for self-driving vehicles. The neural networks figure out how to recognize traffic lights, trees, pedestrians, road signs, and different parts of any random driving environment.

   As an example, Google has started to develop self-driving cars, which use a mix of sensors, light detectors, and other technology, like GPS and cameras. All the input data are combined and the artificial system predicts what those objects might do next. This whole process happens in a matter of milliseconds. Similar to any human driver, the more experience these systems gain, the better they become at driving. The more data it deals with in its deep learning algorithms, the more choices it will make and the faster those choices will be. 

Internet: <www.eescorporation.com> (adapted).