Holding Pattern Detection for Flight Diversion Management
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Solution Overview
Problem
Conventional methods for managing flight diversions due to weather or congestion lead to increased complexities in air traffic systems, resulting in negative passenger experiences, aircraft wear, crew fatigue, and other issues, as aircraft are often placed in holding patterns without clear diversion strategies.
Innovation Solution
A system utilizing AI and real-time data from flight tracking, weather, and airport operational data to predict and manage flight diversions by identifying aircraft in holding patterns and proactively recommending alternative destinations, thereby reducing delays and congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aircraft are instructed to enter holding patterns to wait for destination airport availability, then the number of diversions is reduced, but air traffic system complexity increases and passenger experience deteriorates
Solution Approach 1:
The system performs preliminary detection of holding patterns by analyzing flight data for characteristic turn patterns before aircraft actually enter holding patterns. This early detection enables proactive management actions to be taken, reducing the need for holding patterns in the first place and thereby reducing system complexity while maintaining diversion reduction benefits
2Reliability
If aircraft are placed in holding patterns to wait for runway availability, then diversions are reduced, but passenger experience and crew fatigue worsen
Solution Approach 1:
By detecting holding patterns early through analysis of turn characteristics in flight data, the system enables air traffic management to take preliminary actions such as redistributing aircraft to different holding locations or coordinating staggered arrivals, thereby reducing holding time and improving passenger experience while maintaining the benefit of reduced diversions
3Reliability
If holding patterns are used to manage flight diversions, then diversion events are reduced, but aircraft wear and fuel consumption increase
Solution Approach 1:
The early detection capability allows the system to implement preliminary management strategies such as optimizing holding pattern locations, coordinating multiple aircraft arrivals in sequences, or identifying alternative destinations before aircraft commit to holding patterns, thereby reducing unnecessary holding time and associated fuel consumption while maintaining diversion reduction
Data Source
AI summary
The present disclosure provides for holding pattern detection and management by identifying from flight data for an aircraft that the aircraft has performed a first turn, followed by a leg traverse, and followed by a second turn in a direction circuitous to the first turn and indicating that the aircraft is in a holding pattern and/or identifying from flight data that the aircraft has passed within a predefined distance of a fixpoint and in response to identifying that the aircraft has performed a turn in a known direction associated with a historical holding pattern charted from the fixpoint, indicating that the aircraft is in a holding pattern.