Low-level air traffic modelling for unmanned aircraft integration
- Resource Type
- Conference
- Authors
- McFadyen, Aaron; Martin, Terry
- Source
- 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) Digital Avionics Systems Conference (DASC), 2016 IEEE/AIAA 35th. :1-7 Sep, 2016
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Aircraft
Atmospheric modeling
Image color analysis
Trajectory
Computational modeling
Analytical models
Data models
- Language
- ISSN
- 2155-7209
This paper presents a new data-driven air traffic modelling and analysis technique that can support operational risk analysis for unmanned aircraft integration. The proposed technique exploits advances in computer vision to autonomously extract and analyse the spatial distribution of arbitrary traffic densities, which can provide the foundation for quantitative and tailored risk assessments. The framework can manage large volumes of air traffic data at very low computational cost, and can be customised for other traffic analysis tasks. This unique approach represents a more natural way to process and visualise air traffic data for use by unmanned aircraft operators, regulators and air navigation service providers considering future airspace environments.