Multi-Direction Registration for 3D Road Reconstruction Using Vehicle-Borne LiDAR and Integrated Navigation System Data

3D road reconstruction plays an essential role in road information extraction; however, the existing 3D point cloud registration methods cannot provide high accuracy and robustness for 3D road reconstruction. We propose a multi-direction registration framework for 3D road reconstruction using vehicle-borne LiDAR and integrated navigation system (INS) data. The framework includes five modules. Module I acquires road point clouds with rough geographical locations. Module II presents a novel key point matching algorithm to reduce the displacement deviation along the travel direction. Module III constructs a dual-plane sliding window to extract curb and pavement point clouds. Module IV develops a plane-to-plane registration algorithm for rough pavement registration. Module V extracts the intersection line between the pavement and curb for curb registration. Experimental results demonstrate that our method can achieve state-of-the-art performance in reconstruction accuracy and technical robustness.