Trajectory-Based Well-Clear Boundaries for UAV Airspace Management
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Solution Overview
Problem
The increasing complexity of maintaining safe distances between manned and unmanned aerial vehicles in airspace due to the proliferation of drones, particularly for smaller UAVs that cannot equip with necessary sensors, and the inefficiency of ground-based radar systems for managing large numbers of UAVs.
Innovation Solution
Implementing on-board sensors and computing devices in aerial vehicles to dynamically calculate and maintain a well clear boundary based on instantaneous and future trajectories, vehicle capabilities, and sensor data, allowing for automated course adjustments to prevent collisions without the need for ground-based sensing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ground-based radar systems are used to maintain well clear boundary, then collision avoidance capability is improved, but system cost and complexity increase significantly
Solution Approach 1:
Each aerial vehicle independently calculates its own well clear boundary and detects objects using its own sensors, eliminating the need for centralized ground-based radar systems. The vehicle serves itself by autonomously determining safe flight paths and detecting potential collisions without external infrastructure support.
Solution Approach 2:
The well clear boundary calculation and object detection functions are extracted from ground-based systems and transferred to individual aerial vehicles. Each vehicle carries out these functions independently using onboard sensors and computing resources, removing the dependency on expensive ground-based radar infrastructure.
2Ease of operation
If static well clear boundary is maintained, then simplicity of operation is improved, but adaptability to different vehicle capabilities deteriorates
Solution Approach 1:
The well clear boundary is transformed from a static fixed distance to a dynamic parameter that adjusts in real-time based on vehicle speed, sensor capabilities, and environmental conditions. The boundary continuously adapts to match the specific performance characteristics of each aerial vehicle while maintaining automated calculation simplicity.
Solution Approach 2:
The well clear boundary parameters are changed from fixed values to variable parameters that depend on vehicle speed, sensor field of view, and other performance characteristics. This allows the system to automatically adapt to different vehicle types and capabilities without requiring manual configuration or complex operational procedures.
3Measurement precision
If larger sensors are equipped to detect required volume of air, then detection capability is improved, but weight and cost increase
Solution Approach 1:
The sensor field of view and detection parameters are dynamically adjusted based on vehicle speed and operational conditions. At higher speeds, the system calculates a larger well clear boundary that accounts for increased stopping distance, optimizing sensor usage without requiring physically larger sensors. The detection capability adapts to match the vehicle's performance characteristics rather than using fixed oversized sensors.
4Ease of operation
If visual flight rules are followed, then ease of operation is improved, but operational duration and range are limited
Solution Approach 1:
Visual flight rules that rely on human operators visually maintaining separation distances are replaced with automated electronic well clear boundary calculations and sensor-based object detection. This substitution removes the limitation of human visual range and allows aerial vehicles to operate beyond line of sight while maintaining automated collision avoidance, thereby extending operational duration and range.
Data Source
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AI summary
Systems and methods for airspace management. One embodiment of an aerial vehicle (104), includes a first sensor (108a) for detecting a lateral field of view of the aerial vehicle (104) and a vehicle computing device (106). The vehicle computing device (106) may include a memory component (140) and a processor (530). The memory component (140) may store logic that, when executed by the processor (530), causes the aerial vehicle (104) to calculate, a detection boundary (306b) for the aerial vehicle (104) to maintain a well clear requirement, wherein the detection boundary (306b) is based on instantaneous trajectory, planned future trajectory, and a capability of the aerial vehicle (104) and utilize the capability of the aerial vehicle (104) and data from the first sensor (108a) to maintain the vehicle (104) within detection boundary (306b). In some embodiments the logic may cause the vehicle (104) to provide an instruction maintain the vehicle (104) within the detection boundary (306b).