Aircraft Holding Pattern Detection for Early Diversion Management
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Solution Overview
Problem
Existing systems struggle to accurately identify and manage aircraft in holding patterns, leading to increased disruptions, passenger discomfort, and operational inefficiencies in air traffic networks.
Innovation Solution
A method and system for detecting aircraft in holding patterns using flight data analysis, including predefined distance, turns, and altitude changes to differentiate between holding patterns and racetrack maneuvers, enabling proactive diversion management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aircraft are instructed to enter holding patterns to avoid diversions, then the need for flight diversions is reduced, but air traffic network complexity and operational inefficiency increase
Solution Approach 1:
The system performs preliminary detection of holding patterns by analyzing flight data patterns (turns, distances, altitudes) before aircraft actually enter holding patterns. This early detection enables proactive management actions to be taken, potentially preventing aircraft from entering holding patterns in the first place, thus reducing both diversions and network complexity
Solution Approach 2:
The system continuously monitors flight data and provides feedback about aircraft behavior patterns. By detecting turns, distances traveled, and altitude changes, the system identifies potential holding pattern entries and feeds this information back to air traffic management systems, enabling dynamic adjustment of flight plans and congestion management
2Reliability
If aircraft are placed in holding patterns to manage congestion, then flight diversions are prevented, but passenger experience and crew conditions deteriorate
Solution Approach 1:
By detecting holding patterns early through analysis of flight data patterns, the system enables air traffic management to take proactive measures before aircraft actually enter holding patterns. This preliminary detection allows for alternative congestion management strategies that avoid the negative impacts of holding patterns on passengers and crew
Solution Approach 2:
The system enables rapid identification and management of aircraft that may enter holding patterns by detecting characteristic flight data patterns (turns, distances, altitudes). This allows air traffic management to quickly intervene and implement alternative solutions, reducing the time aircraft spend in holding patterns or avoiding holding patterns entirely
3Reliability
If holding patterns are used to manage aircraft around destination airports, then flight diversions are reduced, but fuel consumption and aircraft wear increase
Solution Approach 1:
The system detects holding pattern formation early by monitoring flight data patterns, enabling air traffic management to implement alternative routing or scheduling decisions before aircraft enter holding patterns. This prevents unnecessary fuel consumption associated with holding pattern maneuvers
Solution Approach 2:
Continuous monitoring of flight data provides feedback on aircraft behavior and holding pattern formation. This feedback enables dynamic optimization of flight paths and timing, allowing air traffic management to minimize fuel-consuming holding patterns while maintaining effective congestion management
Data Source
AI summary
The present disclosure provides for holding pattern detection and management by detecting an aircraft has traveled at least a predefined distance along a flight path for the aircraft, identifying from flight data for an aircraft that the aircraft has performed maneuvers that may indicate a holding pattern, determining that the aircraft is not in a racetrack pattern, and when the aircraft is not in a racetrack pattern, indicating that the aircraft is in a holding pattern.