Other self-driving cars generally rely on a combination of cameras, sensors and lasers.Īn example is Volvo's self driving cars that rely on around 28 cameras, sensors and lasers.Ī network of computers process information, which together with GPS, generates a real-time map of moving and stationary objects in the environment. They also wrote they were able to beat other approaches for detecting three-dimensional objects that use only LiDAR. The Apple researchers said they were able to get 'highly encouraging results' in spotting pedestrians and cyclists with just LiDAR data. In November last year Apple revealed details of its driverless car system that uses lasers to detect pedestrians and cyclists from a distance. While the units supply depth information, their low resolution makes it hard to detect small, faraway objects without help from a normal camera linked to it in real time. These sensors constantly scan the surrounding areas looking for information, acting as the 'eyes' of the car.
In LiDAR (light detection and ranging) scanning - which is used by Waymo - one or more lasers send out short pulses, which bounce back when they hit an obstacle. They are trained with a wealth of information and vast databases of hundreds of thousands of clips which are processed using artificial intelligence to accurately identify people, signs and hazards.
However, others make use of visible light cameras that capture imagery of the roads and streets. Self-driving cars often use a combination of normal two-dimensional cameras and depth-sensing 'LiDAR' units to recognise the world around them.
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