Rausch, ViktorViktorRauschHansen, AndreasAndreasHansenSolowjow, EugenEugenSolowjowLiu, ChangChangLiuKreuzer, EdwinEdwinKreuzerHedrick, J. KarlJ. KarlHedrick2019-11-062019-11-062017Proceedings of the American Control Conference: 4914-4919 (2017)http://hdl.handle.net/11420/3733Deep neural networks are frequently used for computer vision, speech recognition and text processing. The reason is their ability to regress highly nonlinear functions. We present an end-to-end controller for steering autonomous vehicles based on a convolutional neural network (CNN). The deployed framework does not require explicit hand-engineered algorithms for lane detection, object detection or path planning. The trained neural net directly maps pixel data from a front-facing camera to steering commands and does not require any other sensors. We compare the controller performance with the steering behavior of a human driver.enTechnikConference Paper10.23919/ACC.2017.7963716Other