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Journal of Sensors
Volume 2016 (2016), Article ID 1719230, 11 pages
Research Article

Laser-Based Obstacle Detection at Railway Level Crossings

1ISCTE-Instituto Universitario de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal
2CTS-UNINOVA, Universidade Nova de Lisboa (UNL), 2829-516 Caparica, Portugal
3Instituto de Telecomunicações (IT), 1049-001 Lisboa, Portugal

Received 6 September 2015; Accepted 12 January 2016

Academic Editor: Jesus Corres

Copyright © 2016 Vítor Amaral et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a system for obstacle detection in railway level crossings from 3D point clouds acquired with tilting 2D laser scanners. Although large obstacles in railway level crossings are detectable with current solutions, the detection of small obstacles remains an open problem. By relying on a tilting laser scanner, the proposed system is able to acquire highly dense and accurate point clouds, enabling the detection of small obstacles, like rocks laying near the rail. During an offline training phase, the system learns a background model of the level crossing from a set of point clouds. Then, online, obstacles are detected as occupied space contrasting with the background model. To reduce the need for manual on-site calibration, the system automatically estimates the pose of the level crossing and railway with respect to the laser scanner. Experimental results show the ability of the system to successfully perform on a set of 41 point clouds acquired in an operational one-lane level crossing.