Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
campaigns: list<item: string>
child 0, item: string
axis_span: double
worst_disagreement_frac: double
knots: list<item: struct<sun_altitude_deg: double, spread: double, frac_of_span: double, worst_pose_group: (... 278 chars omitted)
child 0, item: struct<sun_altitude_deg: double, spread: double, frac_of_span: double, worst_pose_group: string, mea (... 266 chars omitted)
child 0, sun_altitude_deg: double
child 1, spread: double
child 2, frac_of_span: double
child 3, worst_pose_group: string
child 4, means: struct<none_plate: double, plate: double, lead: double, none: double, none_ped: double, ped: double>
child 0, none_plate: double
child 1, plate: double
child 2, lead: double
child 3, none: double
child 4, none_ped: double
child 5, ped: double
child 5, all_pose_groups: struct<lead: struct<lead: double, none: double>, ped: struct<none_ped: double, ped: double>, plate: (... 42 chars omitted)
child 0, lead: struct<lead: double, none: double>
child 0, lead: double
child 1, none: double
child 1, ped: struct<none_ped: double, ped: double>
child 0, none_ped: double
child 1, ped: double
child 2, plate: struct<none_plate: double, plate: double>
child 0, none_plate: double
child 1, plate: double
models: struct<P_cont_lead.pt: string, P_cont_ped.pt: string, P_pts3_lead.pt: s
...
: int64, (... 95 chars omitted)
child 0, sha256: string
child 1, harness: struct<map: string, cloudiness: double, weather_settle_ticks: int64, rules_digest: string, notexture (... 62 chars omitted)
child 0, map: string
child 1, cloudiness: double
child 2, weather_settle_ticks: int64
child 3, rules_digest: string
child 4, notexturestreaming: bool
child 5, quality_level: string
child 6, capture_order: string
child 62, ped_sun-30.000.npz: struct<sha256: string, harness: struct<map: string, cloudiness: double, weather_settle_ticks: int64, (... 95 chars omitted)
child 0, sha256: string
child 1, harness: struct<map: string, cloudiness: double, weather_settle_ticks: int64, rules_digest: string, notexture (... 62 chars omitted)
child 0, map: string
child 1, cloudiness: double
child 2, weather_settle_ticks: int64
child 3, rules_digest: string
child 4, notexturestreaming: bool
child 5, quality_level: string
child 6, capture_order: string
child 63, plate_sun+00.000.npz: struct<sha256: string, harness: null>
child 0, sha256: string
child 1, harness: null
child 64, plate_sun+60.000.npz: struct<sha256: string, harness: null>
child 0, sha256: string
child 1, harness: null
child 65, plate_sun-30.000.npz: struct<sha256: string, harness: null>
child 0, sha256: string
child 1, harness: null
to
{'map': Value('string'), 'measured': Value('timestamp[s]'), 'models': {'P_cont_lead.pt': Value('string'), 'P_cont_ped.pt': Value('string'), 'P_pts3_lead.pt': Value('string'), 'P_pts3_ped.pt': Value('string'), 'P_pts_lead.pt': Value('string'), 'P_pts_ped.pt': Value('string')}, 'frames': {'lead_hb_sun-30.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+00.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+00.241.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+01.465.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+02.
...
'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun+60.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun-01.422.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun-29.561.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun-30.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'plate_sun+00.000.npz': {'sha256': Value('string'), 'harness': Value('null')}, 'plate_sun+60.000.npz': {'sha256': Value('string'), 'harness': Value('null')}, 'plate_sun-30.000.npz': {'sha256': Value('string'), 'harness': Value('null')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
campaigns: list<item: string>
child 0, item: string
axis_span: double
worst_disagreement_frac: double
knots: list<item: struct<sun_altitude_deg: double, spread: double, frac_of_span: double, worst_pose_group: (... 278 chars omitted)
child 0, item: struct<sun_altitude_deg: double, spread: double, frac_of_span: double, worst_pose_group: string, mea (... 266 chars omitted)
child 0, sun_altitude_deg: double
child 1, spread: double
child 2, frac_of_span: double
child 3, worst_pose_group: string
child 4, means: struct<none_plate: double, plate: double, lead: double, none: double, none_ped: double, ped: double>
child 0, none_plate: double
child 1, plate: double
child 2, lead: double
child 3, none: double
child 4, none_ped: double
child 5, ped: double
child 5, all_pose_groups: struct<lead: struct<lead: double, none: double>, ped: struct<none_ped: double, ped: double>, plate: (... 42 chars omitted)
child 0, lead: struct<lead: double, none: double>
child 0, lead: double
child 1, none: double
child 1, ped: struct<none_ped: double, ped: double>
child 0, none_ped: double
child 1, ped: double
child 2, plate: struct<none_plate: double, plate: double>
child 0, none_plate: double
child 1, plate: double
models: struct<P_cont_lead.pt: string, P_cont_ped.pt: string, P_pts3_lead.pt: s
...
: int64, (... 95 chars omitted)
child 0, sha256: string
child 1, harness: struct<map: string, cloudiness: double, weather_settle_ticks: int64, rules_digest: string, notexture (... 62 chars omitted)
child 0, map: string
child 1, cloudiness: double
child 2, weather_settle_ticks: int64
child 3, rules_digest: string
child 4, notexturestreaming: bool
child 5, quality_level: string
child 6, capture_order: string
child 62, ped_sun-30.000.npz: struct<sha256: string, harness: struct<map: string, cloudiness: double, weather_settle_ticks: int64, (... 95 chars omitted)
child 0, sha256: string
child 1, harness: struct<map: string, cloudiness: double, weather_settle_ticks: int64, rules_digest: string, notexture (... 62 chars omitted)
child 0, map: string
child 1, cloudiness: double
child 2, weather_settle_ticks: int64
child 3, rules_digest: string
child 4, notexturestreaming: bool
child 5, quality_level: string
child 6, capture_order: string
child 63, plate_sun+00.000.npz: struct<sha256: string, harness: null>
child 0, sha256: string
child 1, harness: null
child 64, plate_sun+60.000.npz: struct<sha256: string, harness: null>
child 0, sha256: string
child 1, harness: null
child 65, plate_sun-30.000.npz: struct<sha256: string, harness: null>
child 0, sha256: string
child 1, harness: null
to
{'map': Value('string'), 'measured': Value('timestamp[s]'), 'models': {'P_cont_lead.pt': Value('string'), 'P_cont_ped.pt': Value('string'), 'P_pts3_lead.pt': Value('string'), 'P_pts3_ped.pt': Value('string'), 'P_pts_lead.pt': Value('string'), 'P_pts_ped.pt': Value('string')}, 'frames': {'lead_hb_sun-30.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+00.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+00.241.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+01.465.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'lead_sun+02.
...
'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun+60.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun-01.422.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun-29.561.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'ped_sun-30.000.npz': {'sha256': Value('string'), 'harness': {'map': Value('string'), 'cloudiness': Value('float64'), 'weather_settle_ticks': Value('int64'), 'rules_digest': Value('string'), 'notexturestreaming': Value('bool'), 'quality_level': Value('string'), 'capture_order': Value('string')}}, 'plate_sun+00.000.npz': {'sha256': Value('string'), 'harness': Value('null')}, 'plate_sun+60.000.npz': {'sha256': Value('string'), 'harness': Value('null')}, 'plate_sun-30.000.npz': {'sha256': Value('string'), 'harness': Value('null')}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Camera frames and trained networks for the braking verification study
The inputs to AD-Assurance-Lab/formal-verification--aeb--code, measured on 2026-09-10.
Why this exists. The study's results are in git. These files are not: they are large and git ignores them. Without them the published numbers can be reproduced in kind but never exactly, because the simulator does not render bit-identical frames from one run to the next. Different frames give different networks, which give different certificates.
What is here
captures/Town01/ |
66 frame sets, one per scenario and sun altitude, plus the campaign manifests |
models/Town01/ |
6 trained networks, three policies for each of two scenarios |
MANIFEST.json |
a hash of every file, and the capture harness recorded inside every frame set |
How the pieces fit
A frame set is a rendered approach at one sun altitude: images, the range to the conflict point at each pose, and a stamp saying what made it. The stamp records the map, the cloud cover, the settle time, the determinism rules digest, the texture streaming and quality settings, and the order the knots were captured in. That last field exists because capture order silently ruined a dark endpoint once and nothing recorded it.
The networks are what the certificates are computed on. Each certificate in the code
repository names its network by hash, and those hashes are in MANIFEST.json. If they do
not match, the certificate and the network are not a pair and nothing may be concluded from
them together.
Using them
Clone the code repository, put these directories at results/captures/ and
results/models/, then:
python -m study.status # where the study stands
python tools/family_fidelity.py # how much light each piece of the range spans
Both run without a simulator.
Training reproduces exactly from these frames. Four separate runs gave byte-identical checkpoints. So the networks here can be regenerated from the frames here, and the certificates from the networks. The chain is only broken if the frames are lost.
What the study found
Three policies differing only in which light levels their training frames came from. All three pass all three lighting conditions the standard tests, ten times out of ten, so the standard's own procedure cannot tell them apart.
Driven at 65 light levels between those conditions, three repetitions each: the policy trained on the whole range crashes 0 times, and the policy trained on the regulatory test points crashes 21 times on the lead-vehicle scenario and 9 on the crossing pedestrian. A certificate names those light levels without simulating them.
Method and results: AD-Assurance-Lab/formal-verification--aeb--code, docs/STUDY_REPORT.md.
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