Aircraft Intent Processor Residual Calculation
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Solution Overview
Problem
Current air traffic management systems face challenges in accurately predicting aircraft trajectories, which limits capacity and safety in congested airspace, and fails to accommodate operator-preferred routes and environmental considerations.
Innovation Solution
An aircraft intent processor that calculates residual data to compare actual aircraft states with intended states, enabling better correspondence between predicted and actual trajectories, and facilitating more accurate trajectory predictions and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current air traffic management systems use standard routes (STAR/SID) for aircraft, then safety and separation are maintained, but trajectory prediction accuracy and operator preference accommodation are limited
Solution Approach 1:
The system continuously compares predicted aircraft trajectories with actual trajectories and uses this feedback to improve prediction accuracy. The trajectory prediction module receives actual aircraft state data and adjusts predictions based on the difference between predicted and actual positions, enabling more accurate forecasting while accommodating operator-preferred routes.
Solution Approach 2:
The system transitions from fixed standard route parameters to dynamic trajectory parameters that can be continuously adjusted. By representing aircraft intent as flexible four-dimensional trajectories (position, velocity, attitude, weight over time) rather than rigid standard routes, the system achieves both accurate prediction and accommodation of operator preferences through parameter optimization.
2Productivity
If air traffic management increases aircraft separation to maintain safety, then safety is preserved, but air traffic capacity and throughput are reduced
Solution Approach 1:
The system replaces the mechanical constraint of fixed standard routes with a computational trajectory prediction and optimization system. By using advanced algorithms to predict and adjust aircraft trajectories in real-time, the system can maintain smaller separations while preserving safety, thereby increasing air traffic capacity without compromising reliability.
3Adaptability or versatility
If aircraft follow fixed standard routes, then trajectory predictability is improved, but environmental impact reduction and flexibility are compromised
Solution Approach 1:
The system makes aircraft trajectories dynamic rather than static by continuously optimizing paths based on real-time conditions. The trajectory prediction module adjusts aircraft paths dynamically to minimize environmental impact (noise and emissions) while maintaining flexibility for operator preferences, replacing rigid standard routes with adaptive optimized trajectories.
Data Source
AI summary
Example aircraft intent processors are described herein that can be used both for the prediction of an aircraft's trajectory from aircraft intent, and the execution of aircraft intent for controlling the aircraft. An example aircraft intent processor includes an aircraft intent input to receive aircraft intent data representative of aircraft intent instructions, an aircraft state input to receive state data representative of a state of the aircraft, and a residual output. The aircraft intent processor is to calculate residual data representative of an error between a state of the aircraft commanded by the received aircraft intent data and the state of the aircraft expressed by received state data, and output the residual data via the residual output.