3D-LIDAR based branch estimation and intersection location for autonomous vehicles

It is crucial for autonomous vehicles to navigate at intersections. The accurate location of intersections and the orientation of each branches are necessary for decision making and path planning. In this paper, a unified method is proposed to estimate orientations of each branch at an intersection and to locate the position of the intersection. First, based on vehicle dynamics, a densifying method is used to obtain dense point-cloud data using 3D-LIDAR sensor. Then, according to the data of Open Street Map, the regions-of-interest are extracted and the points are interpolated to transform into an elevation image. Finally, a support vector regression model is employed to estimate the position and orientation of each branch and a fusion method is used to locate the intersection. The experimental results demonstrate the accuracy and robustness of the proposed algorithm.