Aircraft Terminal Congestion Detection Using ADS-B Data
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Solution Overview
Problem
Airport terminal area congestion and resulting flight delays and fuel inefficiencies due to prevailing weather, runway conditions, and flight schedules, which existing technologies have not effectively addressed.
Innovation Solution
A method and system onboard an aircraft that uses aircraft transponder data, specifically Automatic Dependent Surveillance—Broadcast (ADS-B) messages, to compute a terminal congestion coefficient, indicating the level of air traffic, thereby informing flight crews about congestion conditions and optimizing landing decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aircraft wait in holding patterns due to terminal airspace congestion, then safety is maintained by spacing aircraft, but flight delays and fuel consumption increase
Solution Approach 1:
The system performs preliminary detection of terminal area congestion using ADS-B data from multiple aircraft before the subject aircraft enters the holding pattern. By computing congestion coefficients and predicting future congestion levels, the system enables flight crews to make informed decisions about alternative airports or routing in advance, avoiding unnecessary holding patterns and reducing delay time while maintaining safety through proactive planning
Solution Approach 2:
The system continuously receives ADS-B position data from multiple aircraft in the terminal area, computes real-time congestion coefficients, and provides feedback to the flight crew about current and predicted congestion levels. This feedback loop enables dynamic decision-making, allowing crews to adjust their plans based on actual traffic conditions and predictions, thereby reducing unnecessary holding time while maintaining safe separation
2Ease of operation
If aircraft maintain position in holding patterns to manage terminal airspace traffic, then air traffic control is simplified, but fuel efficiency deteriorates
Solution Approach 1:
The system computes congestion coefficients and predicts future congestion levels before the aircraft commits to a holding pattern. By providing advance warning of congested terminal areas and alternative options, the system enables flight crews to select more efficient routing or alternative airports proactively, avoiding fuel-wasting holding patterns while allowing ATC to maintain simplified control of aircraft that do require holding
Solution Approach 2:
The congestion detection system acts as an intermediary between ATC and flight crews, providing processed congestion information and predictions that enable crews to make fuel-efficient decisions independently. This intermediary function reduces the need for extensive holding patterns by enabling proactive route selection, thereby reducing fuel burn while maintaining ATC's simplified control structure
3Measurement precision
If real-time aircraft position data is collected from multiple sources to compute congestion coefficients, then congestion detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system utilizes ADS-B data that is already being broadcast by aircraft for other purposes (position reporting, navigation). By repurposing this existing multi-functional data for congestion detection, the system achieves high measurement precision without adding significant complexity, as the same data infrastructure serves multiple functions including the congestion coefficient computation
Solution Approach 2:
The system leverages the existing ADS-B data infrastructure and aircraft transponders that are already providing position information for other operational purposes. By using this self-generated data from the aircraft fleet without requiring additional dedicated sensing equipment, the system achieves accurate congestion detection while minimizing added system complexity
Data Source
AI summary
A method for evaluating landing conditions at an airport is provided. The method obtains, by an avionics system onboard a first aircraft, aircraft position data associated with a plurality of aircraft located within a range of the airport; and computes a terminal congestion coefficient for the airport, based on the aircraft position data, wherein the terminal congestion coefficient indicates a level of air traffic within the range of the airport.