Pilot Attention Monitoring With Remote Handoff and Autonomous Response
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Solution Overview
Problem
Existing aviation systems lack effective methods to monitor and address pilot inattentiveness, which can lead to dangerous situations, especially in single-pilot operations and complex flight scenarios, and current technologies struggle to ensure pilot attentiveness and safety in various flight regimes.
Innovation Solution
A system and method for pilot attention monitoring that generates data using onboard and remote sensors, determines pilot attention states, and responds to inattentiveness by engaging the pilot, handing off command responsibility to a remote pilot, or autonomously controlling the aircraft, thereby ensuring continuous attentiveness and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pilot attention monitoring is implemented using multiple sensors and data sources, then measurement precision of pilot attention state is improved, but device complexity increases
Solution Approach 1:
The system segments the attention monitoring function into multiple independent sensor modules (eye tracking, head tracking, biometric sensors, flight controller data) that can be independently implemented and combined. Each sensor type monitors a specific aspect of pilot state, and their data is integrated through a validation interface rather than requiring a single complex monitoring system.
Solution Approach 2:
The system uses a multi-functional architecture where a single validation interface processes data from diverse sensor types (optical sensors, biometric sensors, flight controllers) and multiple data sources (telemetry systems, communication systems). This universal interface handles various input formats and triggers different response actions, reducing the need for separate processing systems for each sensor type.
2Reliability
If automated responses are implemented for pilot inattentiveness, then reliability of aircraft operation is improved, but device complexity increases
Solution Approach 1:
The system pre-configures multiple response actions (alerts, warnings, automated control) that are triggered based on predetermined attention state thresholds. When the validation interface determines a specific attention state, the corresponding pre-programmed response is automatically executed, eliminating the need for complex real-time decision-making logic and reducing control system complexity while maintaining high reliability.
Solution Approach 2:
The system implements a feedback loop where pilot responses to alerts and warnings are monitored and fed back into the attention state determination process. This feedback mechanism allows the system to adjust its monitoring and response strategies based on pilot behavior patterns, improving reliability by adapting to individual pilot characteristics while using standardized feedback processing routines that don't significantly increase system complexity.
3Loss of information
If continuous pilot monitoring is performed, then loss of information regarding pilot state is reduced, but use of energy increases
Solution Approach 1:
The system performs attention state validation periodically rather than continuously, with the validation interface checking pilot state at predetermined time intervals or based on specific trigger events (e.g., flight regime changes, communication events). This periodic monitoring approach maintains adequate situational awareness and reduces information loss while significantly lowering the energy consumption compared to continuous monitoring of all sensor streams.
Solution Approach 2:
The system monitors only the most critical attention-related parameters continuously (such as basic eye-open/closed state from optical sensors) while performing more comprehensive analysis of additional parameters (biometric data, detailed flight controller information) only when needed or at reduced frequency. This selective monitoring strategy ensures essential information is never lost while minimizing the overall energy consumption of the monitoring system.
Data Source
AI summary
The method S100 can include: generating pilot monitoring data S110; determining a pilot attention state based on the sensor data S120; optionally determining an aircraft state S130; responding to an event based on the pilot attention state S140; and can optionally include controlling the aircraft based on the aircraft state and the pilot attention state S150. However, the method S100 can additionally or alternatively include any other suitable set of elements. The method functions to facilitate human-in-the-loop aircraft control by an attentive pilot-in-command (PIC). Additionally or alternatively, the method can function to identify and/or resolve pilot inattentiveness (e.g., based on the context of the aircraft state).