Datasets:

ClarusC64
/

autonomous-driving-multisensor-coherence-baseline-modeling-v0.1

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Failed to parse string: 'base+align+corr+band+tol+conf' as a scalar of type double
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2224, in cast_table_to_schema
                  cast_array_to_feature(
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2086, in cast_array_to_feature
                  return array_cast(
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1949, in array_cast
                  return array.cast(pa_type)
                         ^^^^^^^^^^^^^^^^^^^
                File "pyarrow/array.pxi", line 1135, in pyarrow.lib.Array.cast
                File "/usr/local/lib/python3.12/site-packages/pyarrow/compute.py", line 412, in cast
                  return call_function("cast", [arr], options, memory_pool)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/_compute.pyx", line 604, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 399, in pyarrow._compute.Function.call
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Failed to parse string: 'base+align+corr+band+tol+conf' as a scalar of type double
              
              The above exception was the direct cause of the following exception:
              
              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 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, 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 1919, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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id string	scene_context string	ego_state_summary string	camera_summary string	lidar_summary string	radar_summary string	map_localization_summary string	baseline_coherence_score float64	expected_sensor_alignment string	cross_modal_correlation string	stability_band float64	drift_tolerance float64	baseline_confidence string	notes string	constraints string	gold_checklist null
MSCB-001	clear day; highway; light traffic	60mph steady; lane keep stable	2 vehicles ahead; clear lane lines	2 clusters match vehicles; clean ground plane	2 targets match range-rate	map match high; lane geometry consistent	0.86	cam-lidar-radar consistent on lead vehicles; map agrees with lane	0.82,0.80-0.92"	0.1	0.84	High agreement typical	Under 240 words	base+align+corr+band+tol+conf	null
MSCB-002	urban; dusk; moderate traffic	22mph stop-go; frequent braking	lane lines weak; pedestrian silhouettes	clusters stable; edges clear	targets noisy near metal signs	map match medium; localization jitter small	0.68	lidar anchors objects; camera uncertain; radar partial; map mostly consistent	0.62,0.58-0.76"	0.16	0.72	Lower baseline due to dusk	Under 240 words	base+align+corr+band+tol+conf	null
MSCB-003	rain; highway; moderate traffic	55mph; spray; wipers on	reduced visibility; reflections	point cloud sparse; returns drop	targets stable; range-rate reliable	map match high; localization stable	0.64	radar+map reliable; camera degraded; lidar reduced density	0.58,0.52-0.72"	0.18	0.7	Rain lowers cross-modal agreement	Under 240 words	base+align+corr+band+tol+conf	null
MSCB-004	night; suburban; light traffic	30mph steady; gentle turns	headlight glare; signs bright	clusters clean; curb edges clear	few targets; stable	map match high; good lane edges	0.72	lidar+map align; camera glare acceptable; radar sparse but consistent	0.66,0.60-0.80"	0.15	0.74	Night baseline moderate	Under 240 words	base+align+corr+band+tol+conf	null
MSCB-005	construction zone; day	35mph; narrow lane; cones	cones visible; lane shift markings	cones + barriers dense	radar clutter from barriers	map mismatch expected; temporary geometry	0.58	cam+lidar agree on cones; radar clutter; map divergence tolerated	0.50,0.46-0.70"	0.22	0.66	Map disagreement is normal here	Under 240 words	base+align+corr+band+tol+conf	null
MSCB-006	urban canyon; day	18mph; tall buildings	camera stable; partial sky occlusion	lidar multipath edges; some dropouts	radar multipath ghosts possible	map match medium; localization drift risk	0.6	camera+map partial; lidar less stable; radar noisy; coherence band wider	0.54,0.44-0.70"	0.24	0.62	Canyon expands tolerance	Under 240 words	base+align+corr+band+tol+conf	null

What this dataset tests

Whether a system can model the expected coherence of a sensor suite for a given driving context.

The output is a baseline and tolerance band. This is the reference for later decoherence detection.

Required outputs

baseline_coherence_score
expected_sensor_alignment
cross_modal_correlation
stability_band
drift_tolerance
baseline_confidence

Scoring conventions

all scores range 0 to 1
stability band is a low-high interval
drift tolerance encodes how much map/sensor mismatch is normal in context

Use case

Layer one of Anomaly Detection via System-Wide Decoherence.

Supports:

early decoherence onset detection
sensor health monitoring
graceful degradation triggers

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