Automated Pilot Skill Assessment via Behavior Data Correlation
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Solution Overview
Problem
Current methods for assessing pilot skills in training situations are subjective and labor-intensive, relying heavily on instructor observation, which can lead to inconsistent evaluations and increased workload due to the lack of objective tools for detecting non-technical skills, potentially compromising flight safety.
Innovation Solution
A device and method that collect and analyze endogenous and exogenous data during training sessions to detect observable behavior data, correlating them with predefined analysis sequences to assess technical and non-technical skills, providing objective and comprehensive evaluations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If instructors manually observe and assess pilot skills during training sessions, then skill assessment can be performed, but the assessment becomes subjective and inconsistent
Solution Approach 1:
The patent replaces the manual observation and assessment mechanism (instructor's human judgment) with an automated data processing system that collects, analyzes, and evaluates pilot behavior data objectively. This substitution eliminates subjectivity while maintaining assessment functionality.
Solution Approach 2:
The patent introduces an intermediary automated assessment system that acts as a mediator between the pilot's actions and the evaluation process. This intermediary system processes behavior data through predefined analysis sequences, providing consistent and objective assessments without requiring direct instructor intervention in the evaluation.
2Reliability
If instructors manually detect all observable behavior indicators during training, then comprehensive skill assessment is achieved, but instructor workload becomes excessive
Solution Approach 1:
The assessment system performs self-service by automatically collecting data from multiple sources, processing it through analysis sequences, and generating evaluations without requiring instructor intervention for each observation. The system serves itself in detecting and assessing all behavior indicators.
Solution Approach 2:
The patent replaces the manual detection mechanism (instructor's observation capabilities) with an automated data collection and processing system that can continuously monitor and detect all observable behavior indicators simultaneously, eliminating the bottleneck of manual observation.
3Measurement precision
If multiple observable behavior indicators are monitored for each skill, then assessment accuracy improves, but detection difficulty increases
Solution Approach 1:
The patent segments the complex assessment task into multiple predefined analysis sequences, each corresponding to specific skills and their associated behavior indicators. This segmentation allows the system to process each indicator systematically through dedicated analysis routines, making detection manageable despite the large number of indicators.
Solution Approach 2:
The patent implements preliminary action by pre-defining analysis sequences and criteria for detecting behavior indicators before the training session begins. This preparation enables the system to automatically detect and measure multiple indicators during the session without requiring real-time decision-making, reducing detection difficulty.
4Duration of action of moving object
If training sessions last three to four hours with multiple faults and situations, then comprehensive training is provided, but instructor mental load increases
Solution Approach 1:
The assessment system provides self-service throughout the extended training session by continuously and autonomously collecting data, processing it through analysis sequences, and maintaining evaluations without requiring instructor mental engagement for assessment tasks. This allows the instructor to manage the training scenario while the system handles the assessment workload.
Solution Approach 2:
The patent ensures continuity of useful action by implementing continuous data collection and processing throughout the entire training session. The system continuously monitors pilot behavior, processes data through analysis sequences, and maintains up-to-date assessments without interruption or requiring instructor intervention, enabling comprehensive training over extended periods.
Data Source
AI summary
A method for assessing technical and non-technical skills of an operator, includes a step of collecting endogenous data relating to physical manifestations of the operator, and exogenous data relating to the context of a session; steps, implemented by data processing modules, of: correlating the collected data in order to link endogenous data to exogenous data; detecting, using the correlated data, observable behavior data comprising at least one trigger event parameter and one action parameter; analyzing the observable behavior data in predefined analysis sequences, each predefined analysis sequence being specific to a skill to be assessed, and comprising a trigger event parameter and an action parameter characterizing an expected observable behavior according to a predefined situation, the analysis generating a measurement indicator; assessing the behaviors of the operator, by comparing an observed behavior with an expected reference behavior; assessing each skill of the operator on the basis of the results of the behavior assessments.