Model-Based Estimation of Road Direction in Urban Scenes Using Virtual LiDAR Signals

Several proposed schemes have shown remarkable results in autonomous navigation in actual scenes. However, most schemes are dependent on expensive three-dimensional sensing devices such as 3D LiDAR. To solve this problem, in this study, a novel scheme supporting autonomous movement is proposed, particularly for road direction estimation using Virtual LiDAR signals generated through results of semantic segmentation and geometrical information of the camera. Experimental results using the CARLA simulator and actual images taken at outdoor scenes showed that the proposed scheme achieves accurate results, even when moving obstacles are present on the road.