UAV Traffic Management Using Infrastructure Sensor Networks
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges with size, weight, and power constraints due to onboard cameras and sensors for navigation, and communication interruptions occur when out of line-of-sight from remote pilots or navigation systems.
Innovation Solution
A system utilizing an intelligent sensor node network, such as a street light network, to collect and transmit navigation and parameter data for UAVs, generating flight path data and optimizing routes, reducing the need for onboard sensors and improving communication through infrastructure-based data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If onboard cameras and sensors are used for navigation, then navigation capability is improved, but size, weight and power constraints worsen
Solution Approach 1:
The patent introduces infrastructure-based sensor nodes (street lights, traffic signals, buildings) as intermediaries to provide navigation data. These external sensors act as mediators between the UAV and the navigation system, eliminating the need for heavy onboard sensors while maintaining navigation capability through wireless data exchange.
2Reliability
If line-of-sight communication is used between remote pilot and UAV, then communication reliability is improved, but communication continuity worsens when out of line-of-sight
Solution Approach 1:
The patent deploy s infrastructure communication nodes (street lights, traffic signals, cell towers) as intermediaries to relay data between the UAV and remote pilot. These distributed mediators enable communication continuity by providing multiple transmission paths, allowing the UAV to maintain connection even when out of direct line-of-sight.
3Measurement precision
If more onboard sensors are added for better monitoring, then measurement precision is improved, but device complexity worsens
Solution Approach 1:
The patent uses external infrastructure sensors as intermediaries to provide high-precision position and environmental data. Instead of adding complex onboard sensors, the system leverages the measurement capabilities of existing infrastructure (street lights, traffic signals, buildings) that already possess precise positioning and sensing capabilities.
Solution Approach 2:
The infrastructure sensor nodes serve multiple functions simultaneously: they provide navigation data, communication relay, and environmental monitoring. This multi-functionality eliminates the need for separate specialized onboard sensors for each function, reducing overall system complexity while maintaining measurement precision.
Data Source
AI summary
Systems and techniques to facilitate intelligent unmanned aerial vehicle traffic management via an infrastructure network are presented. In an example, a traffic management system can include a data collection component, a flight path component, and a communication component. The data collection component receives navigation data and parameter data associated with an unmanned aerial vehicle. The navigation data is associated with a starting point and destination for the unmanned aerial vehicle. The parameter data is indicative of information associated with the unmanned aerial vehicle. The flight path component generates flight path data for the unmanned aerial vehicle based on the navigation data, the parameter data and infrastructure network data received from an intelligent sensor node network. The communication component transmits the flight path data to the unmanned aerial vehicle.