AI Traffic Display Management for Cockpit Clutter Reduction
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Solution Overview
Problem
Cockpit displays in aircraft become overly cluttered with air traffic information, making it difficult for pilots to discern true threats to safe navigation, as they are overwhelmed by numerous depictions of nearby aircraft, leading to diminished returns on information presented.
Innovation Solution
The implementation of artificial intelligence and machine learning to selectively minimize obscured traffic information, predict the movement of nearby aircraft, and highlight relevant hazards, using a neural network component within a Traffic Collision Avoidance System to suppress less relevant data and customize displays based on flight parameters and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cockpit displays present all nearby aircraft traffic information, then complete situational awareness is provided, but the display becomes overly cluttered and pilots cannot easily discern true threats
Solution Approach 1:
The patent segments traffic information into multiple priority levels (high, medium, low) based on threat assessment algorithms. High-priority threats are displayed prominently with enhanced visual characteristics, while lower-priority traffic is displayed with reduced visual prominence or suppressed entirely. This segmentation allows pilots to focus on critical threats without being overwhelmed by all traffic data simultaneously.
Solution Approach 2:
The patent applies different display qualities and visual characteristics to different portions of the traffic information based on their threat level. Critical threats receive enhanced visual treatment (brighter colors, larger icons, pulsing effects), while less critical traffic receives standard or reduced visual treatment. This local quality differentiation helps pilots quickly identify and prioritize threats without processing all information uniformly.
2Reliability
If cockpit displays show numerous nearby aircraft, then comprehensive traffic awareness is achieved, but cognitive overload increases and decision-making efficiency decreases
Solution Approach 1:
The patent performs preliminary threat assessment and prioritization of traffic information before it reaches the display. Algorithms continuously evaluate all detected aircraft and pre-categorize them by threat level based on factors such as proximity, relative velocity, and predicted trajectory. This preliminary processing ensures that when pilots view the display, the information is already organized and prioritized, eliminating the need for cognitive filtering during high-stress situations.
Solution Approach 2:
The patent introduces an intelligent processing system as an intermediary between raw traffic data and the pilot. This intermediary system analyzes all traffic information, applies threat assessment algorithms, and presents only the most relevant information to the pilot in a prioritized manner. The intermediary acts as a cognitive assistant that handles the complex processing burden, allowing the pilot to focus on decision-making rather than information filtering.
3Loss of information
If all traffic data is presented without filtering, then no information is lost, but the avionics system consumes excessive computational resources to process and display all elements
Solution Approach 1:
The patent extracts and processes only the most relevant traffic information for display, while still maintaining awareness of all detected aircraft through the processing system. Low-priority traffic data is extracted from the complete dataset but displayed with reduced prominence or suppressed entirely, allowing the system to manage computational resources efficiently while preserving the ability to access complete information when needed.
Solution Approach 2:
The patent dynamically changes display parameters (visibility, visual prominence, update frequency) based on the priority classification of each traffic element. High-priority threats are displayed with high visual prominence and updated frequently, consuming more processing resources. Low-priority traffic is displayed with reduced prominence or suppressed, consuming fewer resources. This parameter adjustment allows the system to optimize energy consumption while maintaining situational awareness.
Data Source
AI summary
There is presented systems and methods to present air traffic and other related hazards on a flight deck display in a manner that presents relevant aircraft that may be of interest to flight deck personnel at a future time, accompanied with decluttering the display by removing information pertaining to aircraft that are of lesser impact to the safe navigation of an ownship aircraft. The improved avionics system of the present invention can make decisions that are more intelligent on how to best present traffic information to a flight crew in a manner that improves upon the prior hardware processes and increases efficiency of operation of the avionics hardware and processing system by presenting relevant information and suppressing unnecessary computation and modification of display elements.