Autonomes Fahren: Wie lernen die Autos von Tesla?


Interessanter Artikel über den Unterschied der Lernmethoden beim Autonomen Fahren zwischen Tesla und Waymo.

As Amir Efrati writes in The Information, “Tesla’s engineers believe that by putting enough data from good human driving through a neural network, that network can learn how to directly predict the correct steering, braking and acceleration in most situations.” How much data is enough? There are currently about 400,000 cars with the Autopilot hardware on the road, and they drive a collective 12.5 million miles per day. The size of the fleet is increasing by over 5,000 cars per week. Tesla is the only company that has anything like this data set. Mr. Eady reports that Google’s Waymo tested supervised imitation learning on a small scale, using data from up to 75,000 miles of driving, with impressive results. Israeli firm Mobileye, which previously supplied equipment for Tesla’s Autopilot, and is now owned by Intel, has achieved some success with reinforcement learning, and released a video showing its system in action on the famously chaotic streets of Jerusalem.

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