Reproducing the PVS dataset in Telemachus format¶
The PVS dataset (Menegazzo & von Wangenheim, 2020 — Curitiba, Brazil) is licensed under CC-BY-NC-ND-4.0, which forbids redistribution of derivative works. As a consequence:
- PVS is not on Zenodo in Telemachus format (unlike AEGIS, STRIDE, RS3).
- You need to download the raw CSVs from Kaggle yourself, then convert
locally with the bundled
teleadapter.
If you just want to try Telemachus on a real IMU-rich dataset without going through Kaggle, reach for AEGIS or STRIDE instead — both ship ready-to-use parquets.
What PVS brings¶
| Property | Value |
|---|---|
| Hardware | InvenSense MPU-9250, 2 sensors per vehicle (left / right) |
| Accel / Gyro / Magneto | 100 Hz ground truth |
| GPS | ~1 Hz |
| Trips | 9 (3 vehicles × 3 drivers × 3 sensor placements) |
| Rows | 1,080,905 |
| Location | Curitiba, Paraná, Brazil — Dec 2019 |
| License | CC-BY-NC-ND-4.0 |
Strong points: 3 placements per trip (dashboard / above-suspension / below-suspension), road surface labels, dual-sensor redundancy. Weak point: can't be republished.
Reproduction — 3 steps¶
The full step-by-step (with Kaggle CLI, expected tree, checksum
verification) lives next to the converter in
datasets/pvs/README.md.
In short:
pip install telemachus kaggle
# 1. Download raw data from Kaggle
kaggle datasets download -d jefmenegazzo/pvs-passive-vehicular-sensors-datasets
unzip pvs-passive-vehicular-sensors-datasets.zip -d /path/to/pvs/
# 2. Convert to Telemachus (pick a placement + side)
tele convert pvs /path/to/pvs/ -o datasets/pvs/ --placement dashboard --side left
# 3. Validate
tele validate datasets/pvs/ --level basic
Citing PVS¶
When you publish results using PVS data, cite both the original dataset and the Telemachus format spec:
- Menegazzo, J. & von Wangenheim, A. (2020). PVS — Passive Vehicular Sensors datasets. Kaggle.
- Edet, S. (2026). Telemachus Specification v0.8. Zenodo. DOI 10.5281/zenodo.19609019.