TrajAir
TrajAir is a general-aviation aircraft trajectory dataset collected by CMU's AirLab (Robotics Institute) around the non-towered Pittsburgh-Butler Regional Airport (ICAO: KBTP), a single-runway GA airport 10 miles north…
Source notes
TrajAir is a general-aviation aircraft trajectory dataset collected by CMU's AirLab (Robotics Institute) around the non-towered Pittsburgh-Butler Regional Airport (ICAO: KBTP), a single-runway GA airport ~10 miles north of Pittsburgh, PA. Data was recorded with an on-site ADS-B receiver (1090 MHz / 978 MHz, plus TIS-B for non-equipped aircraft) over 8 months (18 Sept 2020 - 23 Apr 2021), yielding 111 valid days after excluding downtime, repairs, and no-traffic bad-weather days. Each scene contains aircraft trajectories transformed into an airport-centered inertial frame with x,y,z positions (km), aircraft IDs, and frame timestamps interpolated to 1 Hz via cubic interpolation. Weather context (wind direction/velocity, given as wx, wy components in m/s) is added post-hoc from METAR data produced by the KBTP AWOS system. The data is distributed as delimited text files organized into a full 111_days/ folder, four weekly folders (7days1-4), raw CSVs by collection date, and a processed 70/30 train/test split. It was released with the baseline socially-aware prediction method TrajAirNet (ICRA 2022). This is real physical manned-aircraft data, not simulated.
- Scale
- 2,442 hours
- Formats
- custom
- License
- CC-BY-4.0
- Published
- 2021-09-30
Decision summary
passive_log
Metadata requires review against the official source before publication.
Read the dataset manifest and feature schema.
Release history
Source-backed release timing for this canonical dataset record.
- Release evidence
Dataset series published
Release timing is recorded from official dataset metadata.
Selection readiness
6 evidence dimensions for deciding whether this dataset is ready to inspect, compare, or adopt. This is not a model benchmark.
Catalog evidence · not task performance
70/100
Provisional
2/6 dimensions scored · 35% confidence
Read the evidence behind all 6 dimensions
Access and governance
Access and license are declared by the source.
Schema and signal coverage
No machine-readable schema has been verified yet.
Policy training readiness
Observation/action alignment has not been established.
World-model readiness
World-model observation, geometry, or temporal semantics are not verified.
Failure and recovery readiness
No verified failure/recovery annotation evidence is available yet.
Download and processing readiness
Scale is declared; transfer and processing estimates are not measured.
Review unresolved evidence and next checks
Signal gaps
- Observation / ego video. Not enough evidence is available to classify this signal.
- Gaze / attention. Not enough evidence is available to classify this signal.
- Language intent / task phase. Not enough evidence is available to classify this signal.
- Feedback / correction / failure. Not enough evidence is available to classify this signal.
Next checks
- Read the dataset manifest and feature schema.
- Run a bounded sample audit before assigning Strong readiness.
Loop signals
3/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 5 more signal categories
TrajAir is a general-aviation aircraft trajectory dataset collected by CMU's AirLab (Robotics Institute) around the non-towered Pittsburgh-Butler Regional Airport (ICAO: KBTP), a single-runway GA airport ~10 miles north of Pittsburgh, PA. Data was recorded with an on-site ADS-B receiver (1090 MHz / 978 MHz, plus TIS-B for non-equipped aircraft) over 8 months (18 Sept 2020 - 23 Apr 2021), yielding 111 valid days after excluding downtime, repairs, and no-traffic bad-weather days. Each scene contains aircraft trajectories transformed into an airport-centered inertial frame with x,y,z positions (km), aircraft IDs, and frame timestamps interpolated to 1 Hz via cubic interpolation. Weather context (wind direction/velocity, given as wx, wy components in m/s) is added post-hoc from METAR data produced by the KBTP AWOS system. The data is distributed as delimited text files organized into a full 111_days/ folder, four weekly folders (7days1-4), raw CSVs by collection date, and a processed 70/30 train/test split. It was released with the baseline socially-aware prediction method TrajAirNet (ICRA 2022). This is real physical manned-aircraft data, not simulated.
presentNo decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownTrajAir is a general-aviation aircraft trajectory dataset collected by CMU's AirLab (Robotics Institute) around the non-towered Pittsburgh-Butler Regional Airport (ICAO: KBTP), a single-runway GA airport ~10 miles north of Pittsburgh, PA. Data was recorded with an on-site ADS-B receiver (1090 MHz / 978 MHz, plus TIS-B for non-equipped aircraft) over 8 months (18 Sept 2020 - 23 Apr 2021), yielding 111 valid days after excluding downtime, repairs, and no-traffic bad-weather days. Each scene contains aircraft trajectories transformed into an airport-centered inertial frame with x,y,z positions (km), aircraft IDs, and frame timestamps interpolated to 1 Hz via cubic interpolation. Weather context (wind direction/velocity, given as wx, wy components in m/s) is added post-hoc from METAR data produced by the KBTP AWOS system. The data is distributed as delimited text files organized into a full 111_days/ folder, four weekly folders (7days1-4), raw CSVs by collection date, and a processed 70/30 train/test split. It was released with the baseline socially-aware prediction method TrajAirNet (ICRA 2022). This is real physical manned-aircraft data, not simulated.
presentOpen · CC-BY-4.0 · custom
partialEvidence details and provenance
Official signal claims
Schema and annotations
No machine-readable schema facts are captured.
Sample verification
Pending. Metadata does not prove sample coverage, alignment, or file integrity.
curated official source
Integration notes
- Metadata requires review against the official source before publication.