An autonomous vehicle is a vehicle that can guide itself without human conduction. This kind of vehicle has become a concrete reality and may pave the way for future systems where computers take over the art of driving. An autonomous car is also known as a driverless car, robot car, self-driving car or autonomous vehicle. Two of the most talked about self-driving advancements come from Google and Tesla. They take different approaches: Google is using lidar (a radar-like technology that uses light instead of radio waves) sensor technology and going straight to cars without steering wheels or foot pedals. Self-driving cars combine a variety of sensors to perceive their surroundings, such as radar, lidar, sonar, GPS, odometry and inertial measurement units. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. The current state-of- the-art computer vision techniques for autonomous driving involves deep learning using convolutional neural networks (CNN). Rather than having humans describe objects – lanes, curbs, traffic signs – which the system tries to detect, CNN based deep learning systems analyze vast quantities of images and recognizes patterns of objects. Besides being efficient, CNN-based computer vision is robust, able to handle situations such as inadequate lane markings as well as poor visibility situations caused by inclement weather or poor roadside lighting.
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