Aircraft Collision Detection Using Imaging and AI
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Solution Overview
Problem
Current aircraft collision avoidance systems rely heavily on pilot perception and reaction time, which is insufficient for effectively mitigating bird and drone strikes, posing a significant threat to aviation safety.
Innovation Solution
An airborne object detection system equipped with imaging devices and AI/ML modules that analyze environmental data to identify collision risks, determine collision locations, and autonomously execute avoidance maneuvers by communicating with flight control systems to reduce hazard ratings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional collision avoidance systems rely on pilot perception and reaction, then the system complexity is low, but the effectiveness of mitigating bird and drone strikes is insufficient
Solution Approach 1:
The patent replaces the mechanical system of pilot perception and manual reaction with an automated electronic system comprising imaging devices, object detection algorithms, and flight control system integration. The imaging devices capture visual data of the environment, AI/ML algorithms detect and classify airborne objects (birds, drones), and the flight control system automatically executes avoidance maneuvers, substituting human sensory and motor functions with electronic systems.
Solution Approach 2:
The system enables the aircraft to autonomously detect collision risks and execute avoidance maneuvers without continuous pilot intervention. The object detection system continuously monitors the environment, identifies potential threats, calculates collision risk, and triggers appropriate avoidance actions through flight control system integration, allowing the aircraft to protect itself automatically.
2Loss of time
If the system processes imaging data in real-time to detect collision risks, then the safety response time is reduced, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by continuously capturing and pre-processing imaging data even before a collision threat is identified. The imaging devices continuously scan the environment and the object detection system maintains ready-state algorithms for immediate threat identification, allowing the system to transition from detection to avoidance action more rapidly when a collision risk is identified.
Solution Approach 2:
The system implements feedback mechanisms where the object detection system continuously monitors imaging data, identifies airborne objects, assesses collision risk based on object classification and trajectory analysis, and adjusts avoidance maneuvers in real-time. The flight control system receives continuous feedback on maneuver effectiveness and adjusts the aircraft's flight path accordingly to ensure collision avoidance.
Data Source
AI summary
An airborne object detection system can include one or more imaging devices configured to be disposed on an aircraft and to produce imaging data of one or more portions of an environment surrounding the aircraft, and an object detection system operatively connected to the one or more imaging devices to receive the imaging data. The object detection system can be configured to determine whether there are one or more collision risk objects in the imaging data that will or are likely to collide with the aircraft based on the imaging data. The object detection system can be configured to determine a collision location on the aircraft that the one or more collision risk objects will or are likely to collide with.