Datasets:

devCusto
/

vehicle-motion-sensors-fusion

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 4 new columns ({'Distance', 'Date', 'End odometer', 'Start odometer'}) and 4 missing columns ({'angular_velocity_z_rad_s', 'timestamp', 'angular_velocity_x_rad_s', 'angular_velocity_y_rad_s'}).

This happened while the csv dataset builder was generating data using

hf://datasets/devCusto/vehicle-motion-sensors-fusion/Mileage.csv (at revision c388207e8840416327fd5510190cfade548c5aec), [/tmp/hf-datasets-cache/medium/datasets/12185261598814-config-parquet-and-info-devCusto-vehicle-motion-s-56b5c68f/hub/datasets--devCusto--vehicle-motion-sensors-fusion/snapshots/c388207e8840416327fd5510190cfade548c5aec/Gyroscope.csv (origin=hf://datasets/devCusto/vehicle-motion-sensors-fusion@c388207e8840416327fd5510190cfade548c5aec/Gyroscope.csv), /tmp/hf-datasets-cache/medium/datasets/12185261598814-config-parquet-and-info-devCusto-vehicle-motion-s-56b5c68f/hub/datasets--devCusto--vehicle-motion-sensors-fusion/snapshots/c388207e8840416327fd5510190cfade548c5aec/Mileage.csv (origin=hf://datasets/devCusto/vehicle-motion-sensors-fusion@c388207e8840416327fd5510190cfade548c5aec/Mileage.csv), /tmp/hf-datasets-cache/medium/datasets/12185261598814-config-parquet-and-info-devCusto-vehicle-motion-s-56b5c68f/hub/datasets--devCusto--vehicle-motion-sensors-fusion/snapshots/c388207e8840416327fd5510190cfade548c5aec/Speedometer.csv (origin=hf://datasets/devCusto/vehicle-motion-sensors-fusion@c388207e8840416327fd5510190cfade548c5aec/Speedometer.csv)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Date: string
              Start odometer: double
              End odometer: double
              Distance: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 740
              to
              {'timestamp': Value('string'), 'angular_velocity_x_rad_s': Value('float64'), 'angular_velocity_y_rad_s': Value('float64'), 'angular_velocity_z_rad_s': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 4 new columns ({'Distance', 'Date', 'End odometer', 'Start odometer'}) and 4 missing columns ({'angular_velocity_z_rad_s', 'timestamp', 'angular_velocity_x_rad_s', 'angular_velocity_y_rad_s'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/devCusto/vehicle-motion-sensors-fusion/Mileage.csv (at revision c388207e8840416327fd5510190cfade548c5aec), [/tmp/hf-datasets-cache/medium/datasets/12185261598814-config-parquet-and-info-devCusto-vehicle-motion-s-56b5c68f/hub/datasets--devCusto--vehicle-motion-sensors-fusion/snapshots/c388207e8840416327fd5510190cfade548c5aec/Gyroscope.csv (origin=hf://datasets/devCusto/vehicle-motion-sensors-fusion@c388207e8840416327fd5510190cfade548c5aec/Gyroscope.csv), /tmp/hf-datasets-cache/medium/datasets/12185261598814-config-parquet-and-info-devCusto-vehicle-motion-s-56b5c68f/hub/datasets--devCusto--vehicle-motion-sensors-fusion/snapshots/c388207e8840416327fd5510190cfade548c5aec/Mileage.csv (origin=hf://datasets/devCusto/vehicle-motion-sensors-fusion@c388207e8840416327fd5510190cfade548c5aec/Mileage.csv), /tmp/hf-datasets-cache/medium/datasets/12185261598814-config-parquet-and-info-devCusto-vehicle-motion-s-56b5c68f/hub/datasets--devCusto--vehicle-motion-sensors-fusion/snapshots/c388207e8840416327fd5510190cfade548c5aec/Speedometer.csv (origin=hf://datasets/devCusto/vehicle-motion-sensors-fusion@c388207e8840416327fd5510190cfade548c5aec/Speedometer.csv)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

timestamp string	angular_velocity_x_rad_s float64	angular_velocity_y_rad_s float64	angular_velocity_z_rad_s float64
2023-01-01T00:00:00	-0.002452	0.413621	0.698439
2023-01-01T00:00:00.001000	0.030147	0.396153	0.427022
2023-01-01T00:00:00.002000	0.061531	0.394699	0.519541
2023-01-01T00:00:00.003000	0.221909	0.557228	0.324895
2023-01-01T00:00:00.004000	0.023187	0.253549	0.522991
2023-01-01T00:00:00.005000	0.060223	0.297488	0.426078
2023-01-01T00:00:00.006000	-0.05144	0.386427	0.288974
2023-01-01T00:00:00.007000	0.031904	0.456475	0.485578
2023-01-01T00:00:00.008000	-0.076818	0.343882	0.538919
2023-01-01T00:00:00.009000	-0.110961	0.304674	0.548605
2023-01-01T00:00:00.010000	-0.074815	0.385463	0.539691
2023-01-01T00:00:00.011000	0.035684	0.385025	0.583266
2023-01-01T00:00:00.012000	-0.13209	0.261992	0.800126
2023-01-01T00:00:00.013000	0.066706	0.432961	0.524715
2023-01-01T00:00:00.014000	0.04975	0.386811	0.773854
2023-01-01T00:00:00.015000	-0.083413	0.439703	0.796226
2023-01-01T00:00:00.016000	0.016665	0.434711	0.545939
2023-01-01T00:00:00.017000	0.021134	0.218872	0.440294
2023-01-01T00:00:00.018000	0.131807	0.395635	0.639381
2023-01-01T00:00:00.019000	-0.021198	0.389554	0.78478
2023-01-01T00:00:00.020000	0.19246	0.361018	0.283311
2023-01-01T00:00:00.021000	0.034548	0.42033	0.560149
2023-01-01T00:00:00.022000	0.032837	0.370813	0.607636
2023-01-01T00:00:00.023000	-0.129857	0.341134	0.796743
2023-01-01T00:00:00.024000	-0.24845	0.377771	0.371481
2023-01-01T00:00:00.025000	0.034514	0.331126	0.634747
2023-01-01T00:00:00.026000	-0.085258	0.404614	0.674193
2023-01-01T00:00:00.027000	-0.028651	0.351985	0.483875
2023-01-01T00:00:00.028000	0.057914	0.37173	0.615846
2023-01-01T00:00:00.029000	0.202079	0.277064	0.622692
2023-01-01T00:00:00.030000	0.067336	0.305157	0.728673
2023-01-01T00:00:00.031000	0.065036	0.424711	0.740867
2023-01-01T00:00:00.032000	0.041513	0.496207	0.62123
2023-01-01T00:00:00.033000	0.12839	0.395193	0.603598
2023-01-01T00:00:00.034000	0.345042	0.528468	0.425444
2023-01-01T00:00:00.035000	0.159786	0.43962	0.586004
2023-01-01T00:00:00.036000	-0.006731	0.37407	0.583211
2023-01-01T00:00:00.037000	0.140809	0.51597	0.471326
2023-01-01T00:00:00.038000	0.037633	0.32944	0.676521
2023-01-01T00:00:00.039000	0.209867	0.42219	0.613795
2023-01-01T00:00:00.040000	0.114135	0.408981	0.604308
2023-01-01T00:00:00.041000	0.167342	0.200747	0.634478
2023-01-01T00:00:00.042000	0.225087	0.369889	0.461515
2023-01-01T00:00:00.043000	0.332402	0.5307	0.389944
2023-01-01T00:00:00.044000	0.069769	0.352536	0.634589
2023-01-01T00:00:00.045000	-0.068003	0.349558	0.385675
2023-01-01T00:00:00.046000	-0.026013	0.433587	0.808178
2023-01-01T00:00:00.047000	0.105954	0.210996	0.545946
2023-01-01T00:00:00.048000	0.19916	0.452129	0.533011
2023-01-01T00:00:00.049000	0.133904	0.357329	0.664894
2023-01-01T00:00:00.050000	0.15222	0.304603	0.593882
2023-01-01T00:00:00.051000	0.028465	0.460554	0.76159
2023-01-01T00:00:00.052000	0.179613	0.422271	0.669336
2023-01-01T00:00:00.053000	0.192188	0.506413	0.560053
2023-01-01T00:00:00.054000	-0.031382	0.416888	0.484828
2023-01-01T00:00:00.055000	0.367943	0.399023	0.694944
2023-01-01T00:00:00.056000	0.253029	0.404591	0.407754
2023-01-01T00:00:00.057000	0.200534	0.3742	0.531116
2023-01-01T00:00:00.058000	0.395755	0.308307	0.531237
2023-01-01T00:00:00.059000	0.130963	0.438061	0.491637
2023-01-01T00:00:00.060000	0.213156	0.373841	0.842471
2023-01-01T00:00:00.061000	0.035465	0.452629	0.734189
2023-01-01T00:00:00.062000	0.363565	0.329176	0.635407
2023-01-01T00:00:00.063000	0.259689	0.314904	0.849809
2023-01-01T00:00:00.064000	0.125991	0.389803	0.671587
2023-01-01T00:00:00.065000	0.13639	0.385329	0.556282
2023-01-01T00:00:00.066000	0.298598	0.397471	0.476615
2023-01-01T00:00:00.067000	0.359758	0.369433	0.39263
2023-01-01T00:00:00.068000	0.151173	0.470633	0.431403
2023-01-01T00:00:00.069000	0.289353	0.236099	0.524162
2023-01-01T00:00:00.070000	0.121267	0.33329	0.365635
2023-01-01T00:00:00.071000	0.27602	0.384878	0.324748
2023-01-01T00:00:00.072000	0.222605	0.384249	0.642812
2023-01-01T00:00:00.073000	0.056222	0.355114	0.334222
2023-01-01T00:00:00.074000	0.172738	0.298127	0.495598
2023-01-01T00:00:00.075000	0.310769	0.152553	0.604595
2023-01-01T00:00:00.076000	0.277781	0.438084	0.487756
2023-01-01T00:00:00.077000	0.111393	0.387399	0.38713
2023-01-01T00:00:00.078000	0.130204	0.446109	0.593609
2023-01-01T00:00:00.079000	0.068862	0.211254	0.365825
2023-01-01T00:00:00.080000	0.159219	0.29242	0.61173
2023-01-01T00:00:00.081000	0.262224	0.355424	0.440352
2023-01-01T00:00:00.082000	0.32159	0.249091	0.552681
2023-01-01T00:00:00.083000	0.077364	0.339813	0.509248
2023-01-01T00:00:00.084000	0.265838	0.439249	0.6299
2023-01-01T00:00:00.085000	0.143448	0.301906	0.410606
2023-01-01T00:00:00.086000	0.258044	0.466192	0.540316
2023-01-01T00:00:00.087000	0.442719	0.302114	0.371762
2023-01-01T00:00:00.088000	0.141612	0.427701	0.328525
2023-01-01T00:00:00.089000	0.26725	0.300342	0.496533
2023-01-01T00:00:00.090000	-0.02747	0.473208	0.548839
2023-01-01T00:00:00.091000	0.325552	0.391016	0.52696
2023-01-01T00:00:00.092000	0.227686	0.398135	0.507046
2023-01-01T00:00:00.093000	0.393703	0.283841	0.44954
2023-01-01T00:00:00.094000	0.25908	0.306841	0.580102
2023-01-01T00:00:00.095000	0.334005	0.392994	0.35061
2023-01-01T00:00:00.096000	0.475743	0.406406	0.318376
2023-01-01T00:00:00.097000	0.349262	0.280723	0.501084
2023-01-01T00:00:00.098000	0.358033	0.459952	0.363957
2023-01-01T00:00:00.099000	0.412134	0.370558	0.320394

End of preview.

DriveFusion: Multimodal Vehicle Sensor Dataset

DriveFusion is a real‑world multimodal vehicle sensor dataset combining synchronized GPS, speed, heading, gyroscope (IMU), and odometer data.
The dataset is fully anonymized and ideal for research in trajectory prediction, sensor fusion, vehicle dynamics, time‑series modelling, and driving behaviour analysis.

📦 Dataset Contents

This repository includes:

Speedometer.csv
→ Raw GPS + speed + heading
Gyroscope.csv
→ Raw IMU angular velocity
Mileage.csv
→ Raw odometer logs

🧠 Supported Modalities

GPS: latitude, longitude, altitude, accuracy, satellites
Speedometer: speed (km/h), movement flag
Heading: compass direction
Gyroscope (IMU): angular velocity (x, y, z)
Odometer: cumulative distance

🔧 Merging Datasets

The unified dataset is created using a consistent and reproducible pipeline:

1. Speedometer timestamps as the base timeline

All rows in the final dataset correspond to GPS timestamps.

2. Gyroscope merged using nearest‑timestamp join

merge_asof(... direction="nearest")
Ensures IMU readings align with the closest GPS timestamp.

3. Mileage merged using forward‑fill interpolation

Odometer values are expanded into a 1‑second timeline and forward‑filled to match GPS timestamps.

📊 Data Fields

From Speedometer.csv

Field	Description
`timestamp`	ISO‑8601 timestamp
`latitude`	GPS latitude
`longitude`	GPS longitude
`speed_kmh`	Vehicle speed (km/h)
`altitude_meters`	GPS altitude
`heading_degrees`	Compass heading
`gps_accuracy_meters`	Estimated GPS accuracy
`satellite_count`	Number of satellites
`is_moving`	1 = moving, 0 = stationary

From Gyroscope.csv

Field	Description
`gyro_x`	Angular velocity X‑axis
`gyro_y`	Angular velocity Y‑axis
`gyro_z`	Angular velocity Z‑axis

From Mileage.csv

Field	Description
`odometer`	Cumulative odometer reading (km)

🧪 Example Usage

from datasets import load_dataset

ds = load_dataset("your-username/drivefusion")

df = ds["train"].to_pandas()
print(df.head())

🎯 Intended Uses

This dataset is suitable for:

GPS trajectory prediction
IMU‑GPS sensor fusion
Vehicle motion modelling
Driving behaviour classification
Predictive maintenance
Time‑series forecasting
Deep learning sequence models (LSTM, Transformer, TCN)
Kalman filtering / SLAM research

⚠️ Limitations

Gyroscope sampling rate may vary depending on hardware
GPS accuracy fluctuates in tunnels or dense urban areas
Mileage data is daily‑level and interpolated to match GPS timestamps

📄 License

This dataset is released under the MIT License, allowing broad reuse with attribution.

🙌 Contributions

Improvements and suggestions are always welcomed

Downloads last month: 12

Total file size:

910 kB