Dataset of Trucks' Anonymized Recorded Driving and Operation
A working installation of conda package manager is required.
First, install the provided environment.
conda env create -f environment.yml
Activate the environment
conda activate dt_cargo
Add the environment as a jupyter kernel.
python -m ipykernel install --user --name=dt_cargo
The overview of the analyzed fleets.
| Column | Data Type | Unit | Description |
|---|---|---|---|
| vehicle_id | int | - | Unique serial id of each vehicle |
| fleet_test_id | int | - | Unique serial id of the fleet the vehicle belongs to |
| gross_vehicle_weight | int | - | Gross Vehicle Weight Rating (without trailer) |
| total_mass_with_trailer | int | kg | Gross Combination Weight Rating (with trailer,equals gross_vehicle_weight if no trailer can be attached) |
| axle_class | int | - | Vehicle class according to [3] |
The overview of track-wise measured and computed data.
| Column | Data Type | Unit | Description |
|---|---|---|---|
| track_id | int | - | Unique serial id of each recorded track (ordered by vehicle_id and start_time) |
| vehicle_id | int | - | Unique serial id of each vehicle |
| tour_id | int | - | Serial id of each tour, assigned to 1..N tracks |
| start_time | timestamptz | - | Start time of the recording with time zone at time of recording |
| stop_time | timestamptz | - | Stop time of the recording with time zone at time of recording |
| distance | int | m | Dis tance driven during track |
| track_gap | float | m | Dis tance gap to following track |
| avg_speed | float | m/s | Average speed |
| max_speed | int | m/s | Maximum speed within track |
| n_signal_loss | int | - | Number of signal loss events during recording |
| d_signal_loss | float | m | Dis tance covered during signal losses |
| r_signal_loss | float | - | Ratio of signal loss distance to recorded distance |
| avg_hdop | float | m | Average horizontal degree of precision during recording |
| home_base | bool | - | End of recording is at home base of fleet operator |
| long_haul | bool | - | End of recording is more than 150 km away from home bases |
| rest_area | bool | - | End of recording is at an unserviced rest area |
| service_area_fuel | bool | - | End of recording is at a service area |
| industrial_area | bool | - | End of recording is in an industrial area |
| cid | int | - | Cluster id of last location in recording. |
Speed and precision data of each individual track with 10Hz sampling. Speed data are stored in speed.zip in the folder speed/{vehicle_id}/{track_id}.csv In this repository only the Example track is provided, please refer to [1] for the full dataset.
| Column | Data Type | Unit | Description |
|---|---|---|---|
| epoch | int | s | Unix timestamp of measurement in time zone “Europe/Berlin” |
| speed | int | m/s | Speed at measurement in m/s |
| hdop | int | m | Horizontal degree of precision during recording [2] |
[1] Zenodo Dataset TODO
[2] u-blox, “MAX-M8 series u-blox M8 concurrent GNSS modules Data Sheet”, UBX-15031506-R05 [Revised May 2019]
[3] Bundesanstalt für Straßenwesen, „Datensatzformat der Achslast- Jahresauswertungen (ALJA)“, 2018. Accessed: 22 nd Jan 2023 [Online]. Available: https://www.bast.de/DE/Statistik/Achslast/Daten/Daten-Beschreibung.pdf
For contributing to the code please contact:
Georg Balke
Institute of Automotive Technology
Technical University of Munich
mail: [email protected]
V1.1
Georg Balke, Lennart Adenaw
DT-CARGO is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/
A human-readable summary can be found under https://opendatacommons.org/licenses/odbl/summary/. Disclaimer: This is not a license. It is simply a handy reference for understanding the ODbL 1.0 — it is a human-readable expression of some of its key terms. This document has no legal value, and its contents do not appear in the actual license. Read the full ODbL 1.0 license text for the exact terms that apply.
Balke,G. and Adenaw, L. "Heavy commercial vehicles' mobility: Dataset of trucks' anonymized recorded driving and operation (DT-CARGO)" https://doi.org/10.1016/j.dib.2023.109246