Drone Traffic Engineering via Network Data Path Modeling
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Solution Overview
Problem
Current air traffic control systems are not scalable to manage the increasing number of drones in airspace, leading to potential congestion and collision risks, as they replicate models from commercial aviation that are not designed to handle the expected volume of drones.
Innovation Solution
Applying network traffic engineering protocols, such as MPLS and segment routing, to model drone flight paths within geographical areas as data networks, allowing for efficient routing, congestion management, and access control, leveraging proven scalability and reliability from networking protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing air traffic control models from commercial aviation are used to manage drones, then the system can handle current traffic volumes, but it cannot scale to manage the expected large number of drones which will exceed system capacity
Solution Approach 1:
The patent segments the airspace into multiple three-dimensional geographic regions with defined boundaries, creating a hierarchical structure that divides the overall air traffic management problem into smaller, more manageable regional segments. This segmentation allows the system to scale by adding regions rather than increasing overall system complexity proportionally.
Solution Approach 2:
The patent introduces geographic region boundaries as intermediary elements between drones and the central air traffic control system. These boundaries act as mediators that automatically manage traffic flow through admission control mechanisms, reducing the computational burden on the central system while maintaining safety and order.
2Quantity of substance
If the number of drones in a certain section of airspace increases, then more drones can operate in that area, but the chances of collisions and accidents increase
Solution Approach 1:
The patent implements preliminary admission control at geographic region boundaries, where drones are evaluated and authorized to enter regions before actually entering. This preliminary action prevents over-congestion from occurring in the first place, maintaining safe density levels and collision avoidance reliability even as overall drone numbers increase.
Solution Approach 2:
The patent creates dynamic traffic engineering rules that can be applied at geographic region boundaries, allowing the system to adaptively manage drone flow in real-time. These dynamic rules adjust traffic patterns, speeds, and admission rates based on current conditions, maintaining safety as drone quantities fluctuate.
Data Source
AI summary
In one embodiment, a method includes receiving a request for a flight path for a drone, the request including information indicative of a source location within a geographical area and a destination location within the geographical area, modeling the geographical area including a plurality of geographical regions as a data network including a plurality of nodes, determining a network data path from a source node of the plurality of nodes corresponding to the source location to a destination node of the plurality of nodes corresponding to the destination location, determining a flight path for the drone based on the network data path, and transmitting data indicative of the flight path for the drone.