In contrast to the usual approach to operating self-driving cars, Nvidia did not program

any explicit object detection, mapping, path planning or control components into this car.

Instead, the car learns on its own to create all necessary internal representations necessary

to steer, simply by observing human drivers.

The car successfully navigates the construction site without the need for creating specialized

detectors for cones or other objects present at the site.

Similarly, the car can drive on the road that is overgrown with grass and bushes without

the need to create a vegetation detection system.

All it takes is about twenty example runs driven by humans at different times of the

day.

Learning to drive in these complex environments demonstrates new capabilities of deep neural

networks.

The car also learns to generalize its driving behavior.

This video includes a clip that shows a car that was trained only on California roads

successfully driving itself in New Jersey .