Tunnel Facility Based Vehicle Localization in Highway Tunnel Using 3D LIDAR
Kyuwon Kim, Jun-Hyuck Im, Gyu-In Jee
Abstract
Vehicle localization in highway tunnels is challenging for autonomous vehicle navigation. The drift error increases because GPS signals from satellites cannot be received inside a highway tunnel. Therefore, map-aided localization is essential for correcting the drift error. However, the environment around the tunnel is composed mainly of elliptical walls, and there are few unique feature points for map matching, unlike the case outdoors. In this paper, we propose a tunnel facility–based precise vehicle localization method for highway tunnels using 3D LIDAR. For vehicle localization, a point landmark map storing the center points of the tunnel facilities and a probability distribution map storing the probability distributions of the lane markings is used. In the proposed method, the tunnel facility points are extracted using 3D LIDAR, and position estimation is conducted using an extended Kalman filter-based navigation filter. The proposed localization algorithm was verified through experiments using actual highway driving data. The experimental results verify that tunnel facility–based vehicle localization yields precise results in various situations.