Conditional imitation learning (CIL) trains deep neural networks, in an end-to-end manner, to mimic human driving. This approach has demonstrated suitable vehicle control when following roads, avoiding obstacles, or taking specific turns at intersections reach a destination. Unfortunately, performance dramatically decreases deployed unseen environments and is inconsistent against varying weathe...