Aircraft Contingency Planning for Sensor-Reliable Autonomous Control
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Solution Overview
Problem
Current vehicle systems lack comprehensive situational awareness and robust control mechanisms, particularly in autonomous aircraft operations, leading to potential safety risks and inefficiencies due to reliance on human pilots and limited sensor redundancy.
Innovation Solution
A system and method that continuously sample and analyze various inputs from sensors and communication modules to determine aircraft conditions, provide guidance for control, and plan for contingencies, using machine learning and redundancy techniques to enhance situational awareness and vehicle control, even in the absence of critical sensors or pilot inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If human pilots are used for vehicle operation, then adaptability and decision-making capability are improved, but reliability deteriorates due to human error and limited situational awareness
Solution Approach 1:
The system segments the decision-making function between human pilots and autonomous vehicle systems. The autonomous system handles routine monitoring, sensor data analysis, and contingency planning, while human pilots focus on high-level decision-making. This segmentation reduces human cognitive load and minimizes errors while maintaining adaptability.
Solution Approach 2:
The system implements continuous feedback loops where sensors monitor vehicle conditions and environmental factors, the autonomous system analyzes this data to detect potential issues, and alerts are provided to pilots for confirmation or correction. This feedback mechanism enhances reliability by verifying autonomous decisions against human judgment.
2Reliability
If sensor redundancy is increased to improve situational awareness, then reliability is improved, but device complexity increases
Solution Approach 1:
The system employs multi-functional sensor arrays that serve multiple purposes simultaneously. For example, sensors can detect both normal flight parameters and anomaly conditions, or serve both navigation and obstacle detection functions. This universal approach improves situational awareness without proportionally increasing system complexity.
Solution Approach 2:
The autonomous system continuously plans for contingencies by pre-processing sensor data to identify potential failures before they occur. By analyzing sensor inputs in advance and preparing contingency plans, the system maintains high reliability with optimized sensor usage rather than excessive redundancy.
3Reliability
If autonomous control systems are implemented to eliminate human error, then reliability is improved, but adaptability deteriorates due to limited situational awareness
Solution Approach 1:
The autonomous system acts as an intermediary between sensors and control mechanisms, continuously analyzing sensor data to detect pilot errors and suggest corrections. Rather than replacing human judgment entirely, the system provides intelligent assistance that enhances both reliability and adaptability by combining machine precision with human intuition.
Solution Approach 2:
The system dynamically adjusts its level of autonomous intervention based on situational complexity. In routine conditions, it operates with high autonomy for reliability, while in novel or complex situations, it increases human involvement to maintain adaptability. This dynamic adjustment optimizes both reliability and situational awareness.
Data Source
AI summary
A method, preferably including: sampling inputs, determining aircraft conditions, and/or acting based on the aircraft conditions. A method, preferably including: sampling inputs, determining input reliability, determining guidance, and/or controlling aircraft operation. A method, preferably including: operating the vehicle, planning for contingencies, detecting undesired flight conditions, and/or reacting to undesired flight conditions. A system, preferably an aircraft such as a rotorcraft, configured to implement the method.