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The dataset generation failed because of a cast error
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 6 new columns ({'radar_available', 'lidar_available', 'hour_of_day', 'split', 'country', 'month'})

This happened while the csv dataset builder was generating data using

hf://datasets/Trazemag/PRECOG-Labels/precog_dataset.csv (at revision ac8e48ac0560e6168a7ddd3169d2548fd1495592), ['hf://datasets/Trazemag/PRECOG-Labels@ac8e48ac0560e6168a7ddd3169d2548fd1495592/danger_labels.csv', 'hf://datasets/Trazemag/PRECOG-Labels@ac8e48ac0560e6168a7ddd3169d2548fd1495592/precog_dataset.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 1837, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              clip_id: string
              is_danger: bool
              min_ttc: double
              country: string
              month: int64
              hour_of_day: int64
              radar_available: bool
              lidar_available: bool
              split: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1305
              to
              {'clip_id': Value('string'), 'is_danger': Value('bool'), 'min_ttc': 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 1361, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 940, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, 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 1839, 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 6 new columns ({'radar_available', 'lidar_available', 'hour_of_day', 'split', 'country', 'month'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Trazemag/PRECOG-Labels/precog_dataset.csv (at revision ac8e48ac0560e6168a7ddd3169d2548fd1495592), ['hf://datasets/Trazemag/PRECOG-Labels@ac8e48ac0560e6168a7ddd3169d2548fd1495592/danger_labels.csv', 'hf://datasets/Trazemag/PRECOG-Labels@ac8e48ac0560e6168a7ddd3169d2548fd1495592/precog_dataset.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.

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End of preview.

PRECOG-Labels: PhysicalAI-AV Danger Labels

Author: Nikhil Upadhyay | MSc Business Analytics | Dublin Business School Project: PRECOG-AV

Overview

Physics-based danger labels for 298,326 clips from the NVIDIA PhysicalAI-AV dataset, mined using Time-to-Collision (TTC) analysis of 3D obstacle parquets. The first danger labelling at this geographic scale: 25 countries.

14,192 danger clips identified (4.76% positive rate)

Files

File Rows Description
danger_labels.csv 298,326 Binary danger flag and min TTC per clip
precog_dataset.csv 298,326 Full metadata: country, split, hour, sensor availability

Geographic Split

Split Countries Clips
Train 20 countries 275,573
Val Austria, Finland, Portugal 16,151
Test Greece, Bulgaria 6,602

Key Findings

  • Danger rates vary 4.7x across countries — Italy 9.9% vs Estonia 2.1%
  • Peak danger window: 13:00 to 15:00 across all countries
  • Mean danger window: 11.18 seconds across 2,177 labelled test clips

Citation

@misc{upadhyay2026precog,
  title  = {PRECOG: Proactive Risk and Environmental Cognition for Autonomous Vehicles},
  author = {Upadhyay, Nikhil},
  year   = {2026},
  url    = {https://github.com/TrazeMaG/PRECOG-AV}
}
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