1. Barcelona’s approach procedures to RWY 24R
The ORCI project focuses on the West Parallel Runways configuration at Barcelona Airport, which is the most used configuration, with landing operations conducted on RWY 24R.
Arrivals to this runway are managed through RNAV1 instrument approach procedures known as transitions, which are specifically designed to sequence inbound traffic at high-density airports. An RNAV transition is a published procedure consisting of: 1 initial segment, 1 outbound leg and 1 inbound leg, which links a STAR (from an IAF or some earlier point) to a point from which it is possible to accomplish the final approach segment of an approach procedure to the ILS or equivalent approach.
2. 𝗗𝗮𝘁𝗮 𝗖𝗹𝗲𝗮𝗻𝗶𝗻𝗴 / Trajectory Validation
The ORCI project focuses on landing operations on runway RWY 24R and does not consider operations on other runways. In addition, only flights that perform the transition maneuver and whose trajectories are reasonably similar to the published procedure are included.
To prepare the data for training, it is necessary to carefully clean and select the flight trajectories. Although the trombone procedure is clearly defined, it is not always followed in practice. For example, during periods of low traffic, the trombone may be skipped and aircraft may be guided directly to the initial fix (TEBLA). For this reason, only those flights that closely follow the defined approach procedure have been selected, ensuring that the training data contains representative trajectories. The first two images show trajectories where the transition is not used, while the third image shows trajectories that follow the transition as published.
3. Creating synthetic flights.
The main objective of ORCI is to predict the spacing between two consecutive aircraft at the point where the follower intercepts the localizer. For this purpose, each aircraft is paired with the one immediately ahead, designating the first to land as the preceding aircraft and the second as the follower. For subsequent pairs, the same aircraft may act as a follower in one pair and as the preceding aircraft in the next, depending on its position in the landing sequence.
Since the tool is developed using real traffic data, the range of situations it is exposed to is limited to those that occur in normal operations. However, for ORCI to provide reliable predictions, it must also be able to handle a wider variety of situations, including rare or extreme cases that are not present in historical data.
To overcome this limitation, synthetic training samples are created by shifting the timing of the leading aircraft in each valid flight pair forward or backward by a few seconds, while keeping the following aircraft unchanged and preserving the original 3D trajectories. This allows a single real flight pair to generate multiple scenarios with different spacing conditions.
This process makes it possible to cover a full range of situations, including:
- Real operational situations
- Excessive spacing situations
- Unrealistic situations where the following aircraft overtakes or collides with the leading aircraft
By expanding the original dataset from around 3,200 real flights to approximately 55,000 samples, the tool is exposed to separation values ranging roughly from −2 to 8 NM, enabling it to learn from both tighter and wider spacing scenarios than those observed in real operations.
4. Machine Learning Models: content coming soon.
This section is currently under development.
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