metadata
license: bsd-2-clause
task_categories:
- robotics
- time-series-forecasting
version: 1.0.0
date_published: '2025-05-16'
tags:
- aviation
- amelia
configs:
- config_name: default
data_files: data/traj_data_a10v08/raw_trajectories/*/*.csv
Dataset Overview
The Amelia10 dataset provides air traffic position reports for 10 U.S. airports, including the following airports:
- KBOS (Boston Logan International Airport)
- KDCA (Washington National Airport)
- KEWR (Newark Liberty International Airport)
- KJFK (John F. Kennedy International Airport)
- KLAX (Los Angeles International Airport)
- KMDW (Chicago Midway International Airport)
- KMSY (Louis Armstrong New Orleans International Airport)
- KSEA (Seattle-Tacoma International Airport)
- KSFO (San Francisco International Airport)
- PANC (Ted Stevens Anchorage International Airport)
Given the challenges of raw position data, which can be irregularly sampled, noisy, and include tracks outside active movement areas, this dataset has being interpolated to ensure clean data.
Key Features
- Geographic Filtering: Data is filtered using 3D geofences around each airport, including only reports within a 2000 ft altitude above ground level to focus on operationally relevant airspace.
- Interpolation and Resampling: Position reports are interpolated and resampled at a uniform 1 Hz frequency to provide a consistent temporal resolution, ideal for training trajectory forecasting models.
- Comprehensive Metadata: The dataset captures a wide range of attributes, including spatial, temporal, and kinematic information for each agent.
- Diverse Sampling: Includes 15 randomly selected days per airport, covering a range of seasonal and operational conditions to enhance data representation.
- Scalable Format: Data is provided in per-hour, per-airport CSV files for efficient processing, with over 8.43M unique agents and 1.10B position reports included.
| Field | Units | Description |
|---|---|---|
| Frame | # | Timestamp |
| ID | # | STDDS Agent ID |
| Speed | knots | Agent Speed |
| Heading | degrees | Agent Heading |
| Lat | decimal degs | Latitude of the agent |
| Lon | decimal degs | Longitude of the agent |
| Interp | boolean | Interpolated data point flag |
| Altitude | feet | Agent Altitude (MSL) |
| Range | km | Distance from airport datum |
| Bearing | rads | Bearing Angle w.r.t. North |
| Type | int | Agent Type (0: A/C, 1: Veh, 2: Unk) |
| x | km | Local X Cartesian Position |
| y | km | Local Y Cartesian Position |
Use Cases
This dataset is particularly well-suited for tasks like trajectory forecasting, anomaly detection, and air traffic pattern analysis.