Tunnel Facility-based Vehicle Localization in Highway Tunnel using 3D LIDAR

TL;DR

This paper presents a novel vehicle localization method for highway tunnels using 3D LIDAR, overcoming GPS limitations by utilizing tunnel facility points and lane probability maps with an EKF filter, verified through real-world experiments.

Contribution

It introduces a tunnel facility-based localization approach leveraging 3D LIDAR and point landmark maps, suitable for environments with few feature points, validated by highway driving tests.

Findings

Achieves real-time, precise vehicle localization in tunnels.

Effective in environments with limited feature points.

Validated with actual highway driving data.

Abstract

Vehicle localization in highway tunnels is a challenging issue for autonomous vehicle navigation. Since GPS signals from satellites cannot be received inside a highway tunnel, map-aided localization is essential. However, the environment around the tunnel is composed mostly of an elliptical wall. Thereby, the unique feature points for map matching are few unlike the case outdoors. As a result, it is a very difficult condition to perform vehicle navigation in the tunnel with existing map-aided localization. In this paper, we propose tunnel facility-based precise vehicle localization in highway tunnels using 3D LIDAR. For vehicle localization in a highway tunnel, a point landmark map that stores the center points of tunnel facilities and a probability distribution map that stores the probability distributions of the lane markings are used. Point landmark-based localization is possible regardless of the number of feature points, if only representative points of an object can be extracted. Therefore, it is a suitable localization method for highway tunnels where the feature points are few. The tunnel facility points were extracted using 3D LIDAR. Position estimation is conducted using an EKF-based navigation filter. The proposed localization algorithm is verified through experiments using actual highway driving data. The experimental results verify that the tunnel facility-based vehicle localization yields precise results in real time.