Winter, Hanno
Hanno
Winter
0000-0002-0429-1787
Roth, Michael
Michael
Roth
0000-0002-4812-346X
RailDriVE February 2019 - Data Set for Rail Vehicle Positioning Experiments
TU Darmstadt
2020
Railway
Positioning
Data Set
Train
GNSS
IMU
Sensor Fusion
407-04 Verkehrs- und Transportsysteme, Logistik, Intelligenter und automatisierter Verkehr
407-04 Traffic and Transport Systems, Intelligent and Automated Traffic
380
TU Darmstadt
2020-06-04
2020-03-31
2020-06-04
2020-06-04
en
Dataset
https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2292.2
https://doi.org/10.25534/tudatalib-166.2
Creative Commons Attribution 4.0
<p><strong>Key facts</strong></p>
<ul>
<li><strong>Fields of application:</strong><br /> railway positioning, sensor fusion, sensor models</li>
<li><strong>Available data:</strong><br /> 2x GNSS, 2x IMU, 1x odometer, 2x speed sensors, camera images</li>
<li><strong>Available reference data:</strong><br /> Open GNSS/IMU EKF-fusion solution (loosely coupled), Proprietary GNSS/IMU EKF-fusion solution (tightly coupled), Track-Map</li>
<li><strong>Structure:</strong><br /> This data set follows the data sharing principles of the LRT (localization reference train) initiative that are available at <a href="https://lrt-initiative.org/2020_05_28_lrtdatasetguidelines_v1_2/">lrt-initiative.org</a>.</li>
</ul>
<p><strong>About</strong></p>
<p>We provide a data set that can be used for various rail vehicle positioning experiments. The data were collected using the German Aerospace Center (DLR) research vehicle RailDriVE on a segment of the Braunschweig harbor railway in February 2019.</p>
<p>Several sensors of the RailDriVE equipment and an additional self-sufficient system provided by Technische Universität Darmstadt (TU Darmstadt) were employed, including two GNSS receivers, two inertial measurement units (IMU), and several speed and distance sensors (radar, optical, odometer). Front-facing camera data has been included for documentation purposes.</p>
<p>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 as well as a track map have been included.</p>
<p>The data can be used as a starting point for research work or student theses. Novel and established algorithms for many different sub-problems can be tested on the data, in order to facilitate their comparison and make results and insights more accessible.</p>
<p><strong>Similar data sets</strong></p>
<ul>
<li><a href="https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2529" target="_blank">https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2529</a></li>
<li><a href="https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2530" target="_blank">https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2530</a></li>
</ul>
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<p><strong>Companion paper</strong></p>
<p>For reference to the data set in your research, please cite the companion paper:</p>
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<ul>
<li>M. Roth and H. Winter, "An Open Data Set for Rail Vehicle Positioning Experiments," 23rd International Conference on Intelligent Transportation Systems (ITSC), Sep. 2020</li>
<li>BibTex:
<p style="margin-left: 20px;margin-top: 0px;">@InProceedings{RothWinter2020OpenDataSet,<br/>
<span style="margin-left: 20px;">author = {Roth, Michael and Winter, Hanno},</span><br/>
<span style="margin-left: 20px;">title = {An Open Data Set for Rail Vehicle Positioning Experiments},</span><br/>
<span style="margin-left: 20px;">booktitle = {23rd International {IEEE} Conference on Intelligent Transportation Systems ({ITSC'20})},</span><br/>
<span style="margin-left: 20px;">doi = {10.1109/ITSC45102.2020.9294594},</span><br/>
<span style="margin-left: 20px;">year = {2020}</span><br/>}
</p>
</li>
</ul>
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