UTM Server 3D Grid Conflict Potential for UAV Trajectory Optimization
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Solution Overview
Problem
The integration of unmanned aerial vehicles (UAVs) into the National Airspace System poses challenges for Air Traffic Control due to the increasing number of UAVs, necessitating effective detect and avoid (DAA) methods to ensure safe and efficient operation, as current systems struggle to dynamically adjust trajectories in response to changes such as wind, new aircraft, and mission objectives.
Innovation Solution
A market-based approach using a UAS traffic management (UTM) system that employs a 3D grid cell tessellation to assess conflict potential, where UAVs optimize their trajectories by minimizing conflict likelihood through iterative updates and auctions, leveraging mobile edge computing to facilitate real-time conflict resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized air traffic control system is used to manage increasing UAV traffic, then safety monitoring capability is improved, but system complexity and computational burden increase significantly
Solution Approach 1:
The patent divides the airspace into a 3D grid of cells, where each cell independently calculates conflict potential values. This segmentation allows the complex safety monitoring task to be distributed across multiple independent computational units rather than requiring a single centralized system to process all UAV trajectories simultaneously, reducing overall system complexity while maintaining comprehensive safety monitoring.
Solution Approach 2:
The patent introduces conflict potential values as an intermediary metric that mediates between raw trajectory data and safety decisions. Instead of directly analyzing complex trajectory intersections, the system uses pre-calculated conflict potential values for each grid cell to identify and resolve conflicts, simplifying the computational burden while maintaining safety monitoring effectiveness.
2Reliability
If real-time trajectory optimization is performed for all UAVs, then conflict resolution effectiveness is improved, but computational time and processing requirements increase
Solution Approach 1:
The patent performs preliminary calculations of conflict potential values for all grid cells before UAVs need to make trajectory adjustments. By pre-computing these values based on current trajectories and environmental factors, the system reduces the real-time computational burden to simple comparisons and local optimizations, significantly reducing computational time while maintaining effective conflict resolution.
Solution Approach 2:
The patent focuses optimization efforts on only those grid cells and UAVs that are currently experiencing or approaching conflict conditions, rather than performing full trajectory optimization for all UAVs in the system. This partial action approach reduces computational time by concentrating resources on critical conflict zones while maintaining overall conflict resolution effectiveness.
3Measurement precision
If a 3D grid cell tessellation system is implemented to assess conflict potential, then conflict detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the continuous 3D airspace into discrete grid cells, transforming the complex problem of continuous spatial analysis into a manageable set of discrete cell evaluations. Each cell independently calculates its conflict potential value, which improves detection accuracy by providing fine-grained spatial resolution while reducing overall data processing complexity through modular, parallelizable computations.
Solution Approach 2:
The patent transforms complex trajectory intersection analysis into a simplified parameter comparison task by calculating conflict potential values for each grid cell. This parameter transformation converts a complex geometric problem into a straightforward numerical evaluation, improving detection accuracy while reducing data processing complexity through standardized calculations.
4Productivity
If iterative trajectory updates are performed to minimize conflict potential, then trajectory optimization is improved, but communication overhead between UAVs and UTM server increases
Solution Approach 1:
The patent implements periodic iterative updates where UAVs and the UTM server exchange trajectory information at regular intervals rather than continuously. This periodic action maintains effective trajectory optimization by allowing sufficient time for calculations while reducing communication overhead by eliminating unnecessary continuous data exchange, transmitting only when updates are due or conflicts are detected.
Data Source
AI summary
Methods and systems herein relate to unmanned aerial vehicles (UAVs) avoiding collisions by interacting with servers. Some embodiments of a method include receiving, by an unmanned aircraft system (UAS) traffic management (UTM) server one or more intended trajectories from one or more UAVs; determining, by the UTM server one or more conflicts based on the intended trajectories intersecting over a region monitored by the UTM server; and communicating, by the UTM server the one or more conflicts, the communicating includes assigning a value to each of a plurality of three-dimensional (3D) grid cells representing the region monitored by the UTM server, each value representative of a potential for conflict associated with a grid cell; and transmitting, to the one or more UAVs, value data associated with the plurality of grid cells.