Self-driving cars often use a combination of normal two-dimensional cameras and depth-sensing ‘LiDAR’ units to recognise the world around them.
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.
These sensors constantly scan the surrounding areas looking for information, acting as the ‘eyes’ of the car.
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.
In November last year Apple revealed details of its driverless car system that uses lasers to detect pedestrians and cyclists from a distance.
The Apple researchers said they were able to get ‘highly encouraging results’ in spotting pedestrians and cyclists with just LiDAR data.
They also wrote they were able to beat other approaches for detecting three-dimensional objects that use only LiDAR.
Other self-driving cars generally rely on a combination of cameras, sensors and lasers.
An example is Volvo’s self driving cars that rely on around 28 cameras, sensors and lasers.
A network of computers process information, which together with GPS, generates a real-time map of moving and stationary objects in the environment.
Twelve ultrasonic sensors around the car are used to identify objects close to the vehicle and support autonomous drive at low speeds.
A wave radar and camera placed on the windscreen reads traffic signs and the road’s curvature and can detect objects on the road such as other road users.
Four radars behind the front and rear bumpers also locate objects.
Two long-range radars on the bumper are used to detect fast-moving vehicles approaching from far behind, which is useful on motorways.
Four cameras – two on the wing mirrors, one on the grille and one on the rear bumper – monitor objects in close proximity to the vehicle and lane markings.