Roth, Michael ; Winter, Hanno (2022)
An Open Data Set for Rail Vehicle Positioning Experiments.
23rd International Conference on Intelligent Transportation Systems (ITSC). Rhodes, Greece (20.09.2020-23.09.2020)
doi: 10.26083/tuprints-00020408
Conference or Workshop Item, Secondary publication, Postprint
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Item Type: | Conference or Workshop Item |
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Type of entry: | Secondary publication |
Title: | An Open Data Set for Rail Vehicle Positioning Experiments |
Language: | English |
Date: | 2022 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2020 |
Publisher: | IEEE |
Collation: | 7 ungezählte Seiten |
Event Title: | 23rd International Conference on Intelligent Transportation Systems (ITSC) |
Event Location: | Rhodes, Greece |
Event Dates: | 20.09.2020-23.09.2020 |
DOI: | 10.26083/tuprints-00020408 |
Corresponding Links: | |
Origin: | Secondary publication service |
Abstract: | This paper describes an openly available data set for rail vehicle positioning experiments. The data were collected using the DLR research vehicle RailDriVE on a segment of the harbor railway of Braunschweig, Germany, in February 2019. Several sensors of the RailDriVE equipment and an additional self-sufficient system provided by Technische Universität Darmstadt were employed, including two GNSS receivers, two inertial measurement units (IMU), and several speed and distance sensors (radar, optical, odometer) from the rail domain. Front-facing camera data has been included for documentation purposes. In order to simplify its use, some pre-processing steps were applied to the data, mainly to have common time and coordinate frames. Furthermore, example and reference positioning solutions have been included. The data set is described in detail, with information about the individual sensors and the data set structure (with parameters, raw, pre-processed, and reference data). Our work should be seen as a step towards more open and data-driven research in the rail domain, where experiments are difficult and costly. It is our hope to provide a solid basis for many different research efforts that provide the required technological advances for the rail sector. |
Status: | Postprint |
URN: | urn:nbn:de:tuda-tuprints-204084 |
Additional Information: | Keywords: Sensors, Rails, Global navigation satellite system, Optical sensors, Receivers, Sensor systems, Radar tracking |
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
Divisions: | 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics (from 01.08.2022 renamed Control Methods and Intelligent Systems) |
Date Deposited: | 01 Feb 2022 13:10 |
Last Modified: | 21 Mar 2023 11:18 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/20408 |
PPN: | 491452896 |
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