Robust Road Segmentation of Self-Driving Cars Using Deep Learning

Segmentation of road scenes is a crucial problem in computer vision for autonomous driving. For instance, in order to navigate, an autonomous vehicle needs to determine the drivable area ahead and determine its position on the road with respect to the lane markings. However, the problem is challenging due to the presence of environmental factors like noise, darkness, camera shake, especially in bad weather conditions. In this paper, we present a network with two parts for road segmentation under environmental factors, also in order to simulate environmental factors, we use processed images from KITTI and CamVid datasets. This method is implemented on NVDIA GEFORCE MX150 GPU (4G RAM) and the accuracy arrives at 90.75% under environmental factors.

Keywords:

road segmentation , autonomous driving , environmental factors