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Audi says its engineers had previously trained the neural network with the help of “unsupervised learning.” In contrast to supervised learning, it says, unsupervised learning is a method of learning from observations of circumstances and scenarios that does not require pre-sorted and classified data. The neural network received numerous videos to view of road situations that had been recorded with a stereo camera.
As a result, the network learned to independently understand rules, which it uses to produce 3D information from the images of the mono camera. The project of AEV holds great potential for the interpretation of traffic situations.
Along with the AEV, two partners from the Volkswagen Group are also presenting their own AI topics at the Audi booth for this year’s NIPS. The Fundamental AI Research department within the Group IT’s Data:Lab focuses on unsupervised learning and optimized control through variational inference, an efficient method for representing probability distributions.

An Audi team from the Electronics Research Laboratory of Belmont, California, are demonstrating a solution for purely AI-based parking and driving in car parks and on highways. In this process, lateral guidance of the car is completely carried out through neural networks. The AI learns to independently generate a model of the environment from camera data and to steer the car. This approach, the company explains, requires no highly precise localisation or highly precise map data.