Air Traffic Scenario Impact Estimation via Trajectory Modeling
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Solution Overview
Problem
There is a lack of tools that accurately and consistently compare the operational efficiency of actual air traffic scenarios with alternative synthetic scenarios, making it difficult to predict the impact of modifications on airline operational efficiency.
Innovation Solution
A computer-implemented method and system that uses trajectory modeling and generation engines to compare efficiency metrics such as fuel burn, capacity, and emissions between a baseline air traffic scenario and a hypothetical 'what-if' scenario, incorporating changes like new ATM procedures, traffic density, or different aircraft types, by inferring aircraft behavior from surveillance data and applying the same models to both scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a tool is developed to accurately compare operational efficiency between baseline and alternative air traffic scenarios, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the air traffic scenario comparison into distinct modules: a trajectory modeling engine that processes surveillance data and generates flight paths, a scenario generator that creates alternative situations, and an efficiency metric calculator that computes fuel burn, capacity, and emissions. This modular segmentation enables accurate comparisons while managing system complexity through organized, independent components.
Solution Approach 2:
The system creates synthetic copies of baseline air traffic scenarios to generate alternative situations. By copying the structure and parameters of real scenarios and applying modifications (such as different ATM procedures or traffic density), the system enables precise comparison without requiring additional real-world data collection, thus improving measurement precision without proportionally increasing device complexity.
2Measurement precision
If trajectory modeling technology is used to infer aircraft behavior from surveillance data, then measurement precision is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The trajectory modeling engine acts as an intermediary between raw surveillance data and aircraft behavior variables. It processes radar tracks and surveillance information to infer intermediate parameters such as fuel burn, engine rating, speed schedule, and aircraft configuration. This intermediary processing layer transforms difficult-to-measure behavior variables into quantifiable metrics, improving measurement precision while managing detection difficulty through systematic modeling.
3Stability of the object's composition
If the same trajectory modeling library is used for both baseline and alternative scenarios, then consistency is improved, but device complexity increases
Solution Approach 1:
The trajectory modeling library is designed as a universal engine that handles both baseline air traffic scenarios and alternative synthetic scenarios using the same core algorithms and data structures. This multi-functional approach ensures consistency in how aircraft behavior is inferred and efficiency metrics are calculated across different scenario types, improving stability and consistency while managing complexity through a unified rather than duplicated system.
Data Source
AI summary
Techniques for estimating the impact of new operational conditions in a baseline air traffic scenario are described. For at least one flight, embodiments infer an aircraft intent that fits corresponding flight track data. A reconstructed trajectory is computed using the inferred aircraft intent. For at least one flight in an alternative air traffic scenario, an aircraft intent that fits new operational conditions is generated. The new operational conditions include a new air traffic management operation and a new air traffic procedure, and the generated aircraft intent conforms to the new air traffic management operation and the new air traffic procedure. Embodiments compute a generated trajectory of the at least one flight in the alternative air traffic scenario using the generated aircraft intent and compute trajectory-based analytics on each computed trajectory of the baseline and alternative air traffic scenarios using a set of metrics.