Real Time Driving Context Understanding Using Deep Grid Net A Granular Approach

Download or read book Real-time Driving Context Understanding using Deep Grid Net: A Granular Approach written by Liviu A. MARINA and published by Infinite Study. This book was released on with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerous self-driving cars algorithms rely on grid maps for motion planning, obstacles avoidance or environment perception. Obtained from fused sensory information, the occupancy grids (OGs) are nowadays among the most popular solutions used in series production in automotive industry. In this paper, we extend Deep Grid Net (DGN), a deep learning(DL) system designed for understanding the context in which an autonomous car is driving.We consider this paper a granular approach to DGN method due to the improvements added to the original research.