The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 4, saw 2
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
yield from 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/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 4, saw 2Need 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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Check out the documentation for more information.
COMMTR Figure 6 — Agent-Pilot vs Human Pilots Landing Comparison
This package contains the data used to produce Figure 6 of the manuscript "Agent-Pilot" (submitted to Communications in Transportation Research, manuscript ID COMMTR-2026-0064), specifically Section 4.3.3 "Comparison with Human Pilots".
Figure 6 compares Agent-Pilot against ten trained human pilots on attitude control (pitch and bank angles, Fig. 6a–6b) and lateral tracking accuracy (cross-track error, XTE, Fig. 6c) during the final approach (0.2 nm / last ~0.3 nm segment) at the urban vertiport under clear and fog conditions, in Microsoft Flight Simulator (MSFS) 2024.
Directory structure
commtr_fig6_data/
├── README.md
├── SHA256SUMS
├── human_pilots_landing/ # Figure 6 comparison package (agent + human + figures)
│ ├── city_reset_pitch_bank.csv # Agent-Pilot, Urban Clear, per-trial pitch/bank
│ ├── city_fog_pitch_bank.csv # Agent-Pilot, Urban Fog, per-trial pitch/bank
│ ├── city_reset_xte.csv # Agent-Pilot, Urban Clear, per-trial XTE
│ ├── city_fog_xte.csv # Agent-Pilot, Urban Fog, per-trial XTE
│ ├── time_raw_statistics_0.3nm.csv # HUMAN pilots, last-0.3-nm segment statistics
│ │ # (filename suffix -1 = Clear, -2 = Fog)
│ ├── compare_landing_data.py # script that generates the comparison plots
│ ├── calculate_time_raw_statistics.py
│ ├── pitch_bank_comparison.png/.pdf/.svg # Figure 6a–6b
│ └── xte_comparison.png/.pdf/.svg # Figure 6c
├── agent_pitch_bank_results/ # Agent-Pilot per-trial pitch/bank for ALL 16 scenarios
│ ├── city_reset.csv, city_fog.csv, ... (16 scenario CSVs)
│ └── summary_statistics.csv
└── agent_xte_result/ # Agent-Pilot per-trial XTE for ALL 16 scenarios
├── city_reset.csv, city_fog.csv, ... (16 scenario CSVs)
└── summary_statistics.csv
1. Agent-Pilot data (per-trial metrics)
agent_pitch_bank_results/— per-trial pitch and bank statistics (pitch_abs_mean,pitch_abs_sd,bank_abs_mean,bank_abs_sd,total_rows) for the 16 vertiport–weather scenarios, plussummary_statistics.csv(scenario-level averages).agent_xte_result/— per-trial cross-track-error statistics (MAE,RMSE,SD,Max_XTE,Min_XTE,Max_Left,Max_Right,baseline_length) for the 16 scenarios, plussummary_statistics.csv.
The Urban Clear (city_reset) and Urban Fog (city_fog) rows are the
Agent-Pilot data plotted in Figure 6; they are also copied into
human_pilots_landing/ for the comparison.
2. Human pilots data (n = 10 per condition)
human_pilots_landing/time_raw_statistics_0.3nm.csv — statistics over the
last 0.3 nautical mile segment of each human landing:
pitch_abs_mean,pitch_abs_sd,bank_abs_mean,bank_abs_sdbaseline_length_m,xte_abs_mean_m,xte_abs_sd_m,xte_abs_rmse_m- filename convention:
YYYY-MM-DD-HH-MM<initials>-<n>.csvwhere-1= Clear (Reset) condition and-2= Fog condition.
compare_landing_data.py selects the first 10 trials of each condition
(Clear, Fog) to match the ten human pilots reported in the manuscript and
produces the two comparison figures.
3. Figures
pitch_bank_comparison.png/.pdf/.svg— Figure 6a–6b (pitch & bank, four sub-panels).xte_comparison.png/.pdf/.svg— Figure 6c (XTE MAE / SD / RMSE).
4. Provenance
- Server:
sc2i(10.30.58.120), directory/data2/Chenglin/agent/flight_recorder/. - Raw per-trial flight telemetry (35 Hz recorder) for the full 173 Agent-Pilot
trials is available at
/data2/Chenglin/agent/flight_recorder/agent-pilot-recorder_All173/(5.5 GB) and the successful subset at4.7 GB); these are not included in this package but can be provided on request.agent-pilot-recorder_successfull/(
5. License / citation / contact
- License: to be confirmed before release.
- Citation: please cite the Agent-Pilot manuscript (COMMTR-2026-0064).
- Contact: [author email to be added].
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