Existing vision based supervised approaches to lateral vehicle control are capable of directly mapping RGB images the appropriate steering commands. However, they prone suffering from inadequate robustness in real world scenarios due a lack failure cases training data. In this paper, framework for more robust and scalable model is proposed. The only requires an unlabeled sequence images. traine...