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One of the challenges for autonomous driving in general is to detect objects in the car's camera images. In the Audi Autonomous Driving Cup (AADC), among those objects are other cars, adult and child pedestrians andemergency vehicle lighting. We show that with recent deep learning networks weare able to detect these objects reliably on the limited Hardware of the model cars. Also, the same deep network is used to detect road features like mid lines, stoplines and even complete crossings. Best results are achieved using Faster R-CNNwith Inception v2 showing an overall accuracy of 0.84 at 7 Hz.