Aircraft Collision Avoidance Using Trajectory and Behavior Prediction
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Solution Overview
Problem
At uncontrolled airports, pilots rely on their own judgment to avoid collisions, which can be challenging due to the lack of direct air traffic control, leading to potential risks of aircraft colliding with other vehicles.
Innovation Solution
A computing system on the aircraft models the trajectories of both the aircraft and intruder vehicles using real-time position data, determines intersection and behavior probabilities, and outputs a recommended collision avoidance action based on machine learning models to maintain safe separation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pilots rely on their own judgment to avoid collisions at uncontrolled airports, then operational independence is maintained, but collision risk increases due to lack of air traffic control
Solution Approach 1:
The patent introduces an automated collision avoidance system as an intermediary between pilots and the collision risk. The system includes sensors to detect other aircraft, processors to analyze position data and predict trajectories, and output devices to provide alerts to pilots. This intermediary system handles the complex task of collision detection and assessment, allowing pilots to maintain operational independence while significantly reducing collision risk through automated monitoring and warning.
2Reliability
If automated collision avoidance systems are implemented, then collision risk is reduced, but system complexity increases
Solution Approach 1:
The patent implements a universal collision avoidance system that can detect and assess collision risks with multiple types of intruders (aircraft, birds, debris) using the same sensor and processing architecture. The system performs multiple functions including position detection, trajectory prediction, collision risk assessment, and alert generation within a single integrated platform, reducing the need for separate specialized systems and thereby managing complexity while maintaining high reliability.
Data Source
AI summary
A computing system is configured to receive run-time position data for an intruder vehicle and run-time position data for an aircraft. A trajectory of the intruder vehicle is modeled based at least on the run-time position data for the intruder vehicle. A trajectory of the aircraft is modeled based at least on the run-time position data for the aircraft. The computing system is further configured to determine an intersection probability value that the trajectory of the intruder vehicle and the trajectory of the aircraft intersect. A behavior probability value that comprises a confidence level of a predicted behavior classification for the intruder vehicle is determined based at least on the run-time position data for the intruder vehicle and the run-time position data for the aircraft. Based at least on the intersection probability value and the behavior probability value, the computing system is configured to output a recommended collision avoidance action.