This repo will contains the data of our submitted paper: Roadside GNSS Aided Multi-Sensor Integrated Positioning for Vehicle Positioning in Urban Areas . It is part of the project V2X Cooperative Navigation.
10 Oct 2025: The onboard and roadside GNSS data is online!
16 June 2025: We are pleased to share that our paper has been accepted to IEEE IROS 2025. We are currently organizing our data and will be releasing it soon!
Checkout our demo at Video Link
PTP time synchronization with the GPS source is performed on our vehicle platform while PTP time synchronization with the GPS source is conducted on the RSI side.
The dataset is released as rosbag and the RINEX files.
| name | duration | size | link |
|---|---|---|---|
| vehicle_data_20240312 | 240s | 3.0 GB | ROSBAG, onboard GNSS, GT |
The topics within the rosbag are listed below:
| topic | type | frequency | description |
|---|---|---|---|
| /velodyne_points | sensor_msgs/PointCloud2 | 10Hz | Velodyne_HDL32 |
| /imu/data | sensor_msgs/Imu | 400Hz | IMU |
You can download the the Ephemeris data and base station data, e.g. SatRef from Hong Kong Lands Department
Roadside GNSS
| name | ECEF pose | format | link |
|---|---|---|---|
| RSG_roundabout | -2419291.03945686, 5379767.41084528, 2417936.40088097 location | RINEX | Data |
| RSG_west | -2419085.76173037, 5379830.19064999, 2417999.69461309 location | RINEX | Data |
| name | duration | ECEF pose | format | link |
|---|---|---|---|---|
| Rover | 3-hour | -2419083.1267, 5379829.3278, 2418000.2916 location | RINEX | Data |
| RSG_west | 3-hour | -2419085.3593, 5379829.9798, 2417999.3844 location | RINEX | Data |
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Regarding the dynamic data, you can run the baseline based on the GLIO and this config
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Regarding the static data, you can evaluate based on RTKLIB, GraphGNSSLib and GICI
The authors would like to express their thanks to Xikun Liu from PolyU and Alpamys Urtay from ASTRI for their kind help in this research. Thanks for GLIO (Liu, X., Wen, W., & Hsu, L. T. (2023). Glio: Tightly-coupled gnss/lidar/imu integration for continuous and drift-free state estimation of intelligent vehicles in urban areas. IEEE Transactions on Intelligent Vehicles.)