How a Self-Driving Car Learns to Steer From One Camera
A simple neural system turns a single front camera into a driver.
It looks at camera images and outputs steering directions, learning from modest human examples.
The result is a car that learns to handle highways, neighborhood streets, even parking lots and rough roads where markings are missing.
The network figures out useful road cues by itself, it never was told to find lane lines or road edges yet it still finds them.
Because everything is learned together the whole system often works better and gets smaller than designs that split the job up.
That means less hand fixing and more automatic tuning for safe driving.
The system runs fast enough for real driving, so decisions come in time for traffic.
This approach shows how plain camera input plus learning can make a car drive on many kinds of roads, with less fuss and fewer parts than you might expect.
It feels like teaching a car to see, and then it just drives.
Read article comprehensive review in Paperium.net:
End to End Learning for Self-Driving Cars
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