Diversion Airport Selection System for Pilot Workload Reduction
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Solution Overview
Problem
Pilots face a high workload and increased stress when diverting from a flight plan due to the need to mentally aggregate and analyze numerous pieces of information from different sources for potential diversion airports, which can lead to pilot error in time-sensitive emergency situations.
Innovation Solution
A system that scores and ranks potential diversion airports in real-time based on current aircraft and destination status, using parameter groups to calculate viability scores and display them intuitively on a navigational map, reducing the mental workload by consolidating information and presenting it in a digestible manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the pilot manually aggregates and analyzes information from multiple sources for each potential diversion airport, then the pilot can make an informed decision, but the mental workload and time required increase significantly
Solution Approach 1:
The system automatically performs the information aggregation and analysis tasks that would otherwise require pilot intervention. The diversion airport selection system gathers data from multiple sources (weather, NOTAMs, fuel consumption, time en route) and independently calculates viability scores, eliminating the need for the pilot to manually process each information source while maintaining decision accuracy
Solution Approach 2:
The system introduces an intermediary processing layer between the raw information sources and the pilot decision-making process. This intermediary automatically synthesizes data from weather radar, NOTAMs, SIGMETs, PIREPs, and performance databases, presenting a consolidated view that reduces the cognitive burden on the pilot while preserving the reliability of the decision
2Reliability
If the pilot analyzes multiple diversion airports sequentially, then the most suitable airport can be identified, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary analysis of multiple diversion airports simultaneously rather than sequentially. By pre-calculating viability scores for all candidate airports using current aircraft state and environmental data, the system eliminates the time penalty of sequential analysis while maintaining the quality of selecting the most suitable diversion destination
Solution Approach 2:
The system analyzes more airports than the pilot would typically evaluate manually, presenting a ranked list of viable options. This excessive analysis approach ensures that the optimal diversion airport is identified without requiring the pilot to spend excessive time evaluating each option, as the system has already performed comprehensive assessment
3Loss of information
If comprehensive information from multiple sources is presented to the pilot, then the pilot has complete awareness of the situation, but the information becomes difficult to process and increases stress
Solution Approach 1:
The system segments comprehensive information into organized categories (weather conditions, airport availability, aircraft performance, time and fuel constraints) and presents them as structured parameters. This segmentation maintains complete information while making it easily scannable and processable, reducing pilot stress by eliminating the need to mentally organize data from multiple sources
Solution Approach 2:
The system uses visual indicators such as color-coded viability scores and graphical representations to convey the status of each diversion airport. This visual encoding allows the pilot to quickly grasp critical information at a glance, maintaining complete situational awareness while dramatically improving ease of information processing and reducing cognitive load
Data Source
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AI summary
Methods and systems are provided for presenting a list (402) of potential diversion destinations. One exemplary method involves obtaining status information associated with the vehicle (102), obtaining status information associated with respective ones of a plurality of destinations, and classifying the plurality of destinations into a plurality of viability groups (404, 406, 408) based at least in part on the status information associated with the vehicle (102) and the respective status information associated with each respective destination. Each of the viability groups (404, 406, 408) contains a subset of the plurality of destinations. The method continues by displaying a list (402) of the plurality of destinations on a display device associated with the vehicle (102), with the plurality of destinations being ordered in the list (402) based at least in part on their respective viability group classifications. In this regard, destinations classified into a higher viability group (404) may be preferentially displayed over destinations classified into lower viability groups (406, 408).