Tackling Airspace Congestion: A Scalable and Robust Framework for End-to-End UAS Traffic Management
Published in ITSC 2023, 2023
Abstract
We present an end-to-end air traffic management framework for Unmanned Aircraft Systems (UAS) operations that is both scalable and robust. Our approach involves defining congestion in the airspace and developing a congestion-based cost map that can mitigate potential congestion while adhering to regulations and guidelines. Each UAS operation leverages a recursively updated cost map in solving the path planning problem, providing scalability of the framework. Additionally, we introduce a time-critical controller to enhance the robustness of mission execution. Empirical evidence confirms the feasibility and effectiveness of our method, achieving significant reductions in both cumulative and maximum levels of airspace congestion.Results
Congestion induced with and without RFTT was compared, and an additional limit on its travel distance per time interval was not imposed. This process involves creating a 3D model of the city by comparing off-nadir satellite imagery, and then using edge detection to separate buildings from the terrain in vertical satellite images. Resulting terrain, roadway, and building models are projected vertically into polygons and color-coded based on their respective zoning to generate an airspace capacity map. Using the constructed airspace capacity, we created a congestion map. The paths taken by each UAS were visualized in the following figure. 
