Document worth reading: “A Survey of Deep Learning Techniques for Autonomous Driving”

The closing decade witnessed increasingly quick progress in self-driving vehicle know-how, primarily backed up by advances throughout the house of deep learning and artificial intelligence. The aim of this paper is to survey the current state-of-the-art on deep learning utilized sciences utilized in autonomous driving. We start by presenting AI-based self-driving architectures, convolutional and recurrent neural networks, along with the deep reinforcement learning paradigm. These methodologies sort a base for the surveyed driving scene notion, path planning, conduct arbitration and motion administration algorithms. We study every the modular perception-planning-action pipeline, the place each module is constructed using deep learning methods, along with End2End strategies, which straight map sensory information to steering directions. Additionally, we cope with current challenges encountered in designing AI architectures for autonomous driving, reminiscent of their safety, teaching info sources and computational {{hardware}}. The comparability supplied on this survey helps to realize notion into the strengths and limitations of deep learning and AI approaches for autonomous driving and assist with design selections A Survey of Deep Learning Techniques for Autonomous Driving