Intelligent Drivable Area Detection System using Camera and Lidar Sensor for Autonomous Vehicle

Road detection is the most primary and important task for any autonomous vehicles. Nowadays, most of the cars available in the market have camera sensors which assist the drivers for safe driving. Therefore, we propose a sensor fusion method by utilizing LiDAR and Camera sensor together to develop a robust drivable road detection system. In this paper, the edge detection and color based segmentation techniques has been used to generate the binary image of lanes from camera sensor images. Then the line models is fitted on the generated binary image using RANSAC algorithm to find the lane marking. But there are many roads in urban area where only one side lane marks are present and sometimes no lane marking at all. In such places, the drivable road detection system wouldn't be able to perform well and doesn't know its boundary for the vehicle to drive. The sensor fused method proposed in this paper utilizes the LiDAR sensor information along with camera images to know its trajectory for safe travel. The algorithm works very well in different road scenarios in an urban area where the road has two lane marks, one side lane with other side curb and finally on both side curbs. The proposed method is tested with two different datasets. The overall results show that the proposed algorithm performs robustly well and the system is able to identify its drivable region accurately.