Emergency Landing Decision Support for Low-Altitude Diversions
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Solution Overview
Problem
Legacy aircraft systems lack real-time decision support for emergency landings, particularly at low altitudes, as they do not account for environmental conditions or the aircraft's condition, and rely on ground controllers, leading to time delays that can compromise safe landings.
Innovation Solution
The Low Altitude Diversion Assistant (LADA) system provides pilots with real-time decision support by simulating alternative landing sites, considering environmental conditions and aircraft state, and offering a confidence score for each site, using pre-flight data collection, proactive scenario evaluation, and semantic data federation to prioritize landing options dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If ground controllers manually integrate data and run simulations to provide landing site information, then comprehensive decision support is provided, but time delay increases significantly
Solution Approach 1:
The system enables the aircraft to perform its own emergency landing assessment by automatically collecting data from onboard sensors, evaluating environmental conditions, running simulations, and generating landing site recommendations without requiring ground controller intervention. This self-service approach eliminates time delays while maintaining comprehensive decision support capabilities.
Solution Approach 2:
The system pre-loads airport data, pre-configures simulation parameters, and has ready-to-execute evaluation algorithms before emergencies occur. When an emergency is detected, the system can immediately begin assessments without waiting for ground controller data collection or system initialization, significantly reducing response time.
2Loss of time
If legacy on-board systems automatically select landing sites, then response time is reduced, but they assume fully capable aircraft and do not account for environmental conditions or aircraft state
Solution Approach 1:
The system dynamically adjusts evaluation parameters based on real-time aircraft conditions (engine power, altitude, speed) and environmental factors (wind, weather). This allows the system to provide accurate landing site recommendations for compromised aircraft while maintaining fast response times, unlike legacy systems that assume fully capable aircraft.
Solution Approach 2:
The system continuously monitors aircraft state and environmental conditions, using this feedback to update simulation models and refine landing site recommendations in real-time. This closed-loop approach ensures recommendations remain accurate even as aircraft performance degrades or environmental conditions change during the emergency response period.
3Reliability
If the system runs comprehensive simulations accounting for environmental conditions and aircraft state, then accuracy of recommendations improves, but computational complexity increases
Solution Approach 1:
The system divides the complex simulation task into modular components: data collection from sensors, environmental condition evaluation, aircraft state assessment, simulation execution, and recommendation generation. This segmentation allows parallel processing of independent modules, reducing overall computational complexity while maintaining comprehensive simulation accuracy.
Solution Approach 2:
The system implements a tiered simulation approach where essential simulations provide immediate landing site recommendations, and more comprehensive simulations can be run subsequently for refinement. This partial action approach delivers timely recommendations with sufficient accuracy without requiring all possible simulations to complete before providing guidance.
Data Source
AI summary
A system and method to assist aircraft pilots with rapid decision-making in cases where the pilot needs to make a flight diversion at low altitudes due to an emergency (for example, loss of thrust). Once an emergency need for diversion is detected, the system and method generates a list of alternative airports the plane can reach given: (i) the current conditions of the plane; (ii) a real-emergency time simulation of evolving conditions of the plane; (iii) the environment at potential landing sites; and (iv) the environment on the flight path to those sites. For airports potentially within reach, the system and method provides a confidence scores for successful landings for alternative simulated landing options. The simulations and confidence scores take into account aircraft position, altitude, speed, and possible further problems with the aircraft for the both the current flight path and for each simulated alternative.