Multivariable Airspace Complexity Model for Sector Capacity Optimization
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Solution Overview
Problem
The National Airspace System is overwhelmed due to increasing demand for air transportation, leading to flight delays and cancellations, as current methods only consider the number of aircraft in a sector to assess complexity, failing to account for other influential factors, thus limiting capacity.
Innovation Solution
A system utilizing a multivariable model to assess airspace complexity, allowing for the selection and modification of various variables to reduce sector complexity without decreasing the number of aircraft, thereby increasing capacity, by suggesting adjustments such as altering aircraft headings, speeds, or altitudes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the number of aircraft in a sector is used as the sole measure of complexity, then the assessment method is simple, but the sector capacity cannot be increased because it does not account for other influential factors
Solution Approach 1:
The patent transforms the complexity assessment from a single-parameter system (aircraft count) to a multi-parameter system incorporating variables such as aircraft separation, sector geometry, traffic flow patterns, and weather conditions. This parameter expansion allows for more nuanced complexity evaluation and enables capacity optimization without simply reducing aircraft numbers.
Solution Approach 2:
The patent introduces computational algorithms and multivariable models as intermediaries between raw traffic data and complexity assessment. These intermediaries process multiple variables simultaneously to generate comprehensive complexity metrics, enabling controllers to maintain higher aircraft counts while managing complexity through informed decision-making.
2Device complexity
If the aircraft count is reduced to decrease sector complexity, then the complexity measure is improved, but the sector capacity and throughput are reduced
Solution Approach 1:
Instead of reducing aircraft count to manage complexity, the patent inverts the approach by using multivariable models to identify configurations where higher aircraft counts can be sustained. The system analyzes multiple parameters to find optimal arrangements that maintain acceptable complexity levels while maximizing the number of aircraft that can be safely managed in the sector.
Solution Approach 2:
The patent implements dynamic complexity management where the system continuously monitors multiple variables and adjusts sector capacity recommendations in real-time. Rather than applying a static reduction rule, the system adapts complexity thresholds and capacity recommendations based on current traffic patterns, weather conditions, and other relevant factors.
3Measurement precision
If more variables are included in the complexity model, then the accuracy of complexity assessment is improved, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent segments the complexity assessment into hierarchical levels: core variables that directly impact safety (e.g., aircraft separation, altitude), secondary variables that influence efficiency (e.g., traffic flow patterns, sector geometry), and tertiary variables that provide contextual information (e.g., weather, airspace restrictions). This segmentation allows the system to process variables in priority order and reduces computational burden by focusing resources on the most critical parameters.
Data Source
AI summary
An airspace complexity reducing system is provided. The airspace complexity reducing system has a data storage device including data describing a multivariable model of an airspace complexity, the airspace complexity being a cumulative effect of factors that influence a system user's ability to manage aircraft in an associated airspace. The airspace complexity reducing system also has a selecting module configured to select a variable from a plurality of variables of the multivariable model and determine an amount by which to modify the selected variable to achieve a predetermined airspace complexity value. In addition, the airspace complexity reducing system has a suggestion module configured to determine a modification to the airspace that results in the determined variable modification and transmit the determined course of action to the system user.