Edge DAA Architecture for Low-Latency UAV Traffic Resolution
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Solution Overview
Problem
Current Unmanned Aerial System (UAS) Traffic Management (UTM) systems face challenges in safely and efficiently managing UAV traffic, including collision risks, airspace complexity, and high operation density, which are not adequately addressed by existing technologies.
Innovation Solution
The implementation of a UTM system that incorporates Mobile Edge Computing (MEC) and edge-based Detect and Avoid (DAA) systems, which utilize PIBS messages for trajectory estimation and collision risk prediction, enabling conflict-free group resolution advisories and hybrid DAA processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized UTM systems are used to manage UAV traffic, then traffic management capabilities are provided, but latency in conflict resolution increases and scalability is limited
Solution Approach 1:
The patent segments the centralized UTM system into distributed edge computing nodes deployed at strategic locations (airports, airspaces). Each edge node independently processes conflict detection and resolution for local UAV traffic, eliminating the single-point bottleneck and reducing latency while maintaining comprehensive traffic management coverage.
Solution Approach 2:
The patent introduces a new dimensional architecture by deploying edge computing capabilities across multiple spatial dimensions (different airspaces, airports, and geographic locations) rather than relying on a single centralized point. This multi-dimensional distribution enables parallel processing of conflict resolution tasks, significantly reducing latency.
2Reliability
If centralized UTM systems are used to manage UAV traffic, then traffic management is achieved, but system scalability is limited
Solution Approach 1:
The patent divides the monolithic centralized UTM system into modular edge computing nodes that can be independently deployed, scaled, and managed. Each node handles local traffic management autonomously, allowing the system to scale horizontally by adding more edge nodes to accommodate growing UAV traffic without overloading a central processor.
Solution Approach 2:
The patent implements dynamic scalability by allowing edge computing nodes to be added, removed, or adjusted based on real-time traffic demands. The system can dynamically allocate computational resources across edge nodes, enabling flexible adaptation to varying UAV operation densities and airspace complexity levels.
3Reliability
If edge-based DAA systems are implemented, then collision avoidance capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces standardized communication interfaces and protocols as intermediaries between edge computing nodes and UAVs. These intermediaries simplify the interaction complexity by providing uniform methods for trajectory estimation, conflict detection, and resolution advisory transmission, allowing edge nodes to be deployed without proportionally increasing operational complexity.
Solution Approach 2:
The patent implements universal edge computing node designs that can handle multiple functions (trajectory estimation, conflict detection, resolution generation, and communication) within a single standardized platform. This multi-functionality reduces overall system complexity by eliminating the need for separate specialized systems for each function.
Data Source
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AI summary
An unmanned aerial vehicle (UAV) may detect a risk of collision with one or more objects in an airspace serviced by a mobile edge computing (MEC) node. The MEC node may provide an edge detect and avoid (edge-DAA) function for use in the airspace. The UAV may determine a first resolution advisory (RA) to be acted on in order to avoid the collision with the one or more objects based on a local DAA function within the UAV. The UAV may receive, from the MEC node, a second RA to be acted on in order to avoid the collision with the one or more objects based on the edge-DAA function. If the second RA can be acted on to avoid the collision with the one or more objects, the UAV may act on the second RA and may send a message to the MEC node with an acknowledgement.