Automatic Mapping of Center Line of Railway Tracks using Global Navigation Satellite System, Inertial Measurement Unit and Laser Scanner

Abstract

Up-to-date geodatasets on railway infrastructure are valuable resources for the field of transportation. This paper investigates three methods for mapping the center lines of railway tracks using heterogeneous sensor data: (i) conditional selection of satellite navigation (GNSS) data, (ii) a combination of inertial measurements (IMU data) and GNSS data in a Kalman filtering and smoothing framework and (iii) extraction of center lines from laser scanner data. Several combinations of the methods are compared with a focus on mapping in tree-covered areas. The center lines of the railway tracks are extracted by applying these methods to a test dataset collected by a road-rail vehicle. The guard rails in the test area were also extracted during the center line detection process. The combination of methods (i) and (ii) gave the best result for the track on which the measurement vehicle had moved, mapping almost 100% of the track. The combination of methods (ii) and (iii) and the combination of all three methods gave the best result for the other parallel tracks, mapping between 25% and 80%. The mean perpendicular distance of the mapped center lines from the reference data was 1.49 meters.

Robotic Railway Multi-Sensing and Profiling Unit Based on Artificial Intelligence and Data Fusion

“…The features of the fastener are extracted by determining the similarity of a pair of images. A method for the alignment and centring of the railway track is described in [ 18 ], where a combination of a global navigation satellite system, an inertial measurement unit and a laser scanner is used for increasing the precision to an acceptable level. The combination of the above-described methods gave the best result for the track on which the measurement vehicle had moved in the practical experiments, mapping almost 100% of the track.…”

An Open Data Set for Rail Vehicle Positioning Experiments

“…Based on a 2008 Mercedes Benz Vario, the vehicle is equipped with an extra set of rail wheels and hydraulics that facilitate its operation on both road and rails 1 . Since 2008 the RailDriVE has been used for railrelated research on topics such as positioning [5], condition monitoring [6], communication, and mapping [7]. Fig.…”

“…Different map-supported approaches for positioning include [17]- [21]. Approaches without mapsupport include [7], [22], [23]. Approaches with sensors beyond this data set include [24]- [26].…”