ARLINGTON, VA, February 25, 2021 – Quantitative Scientific Solutions today announced that it is part of a team that has been selected by the U.S. Air Force Agility Prime Small Business Technology Transfer (STTR) Program to develop model-based systems engineering approaches with machine learning for applications in urban air mobility. The project will involve developing a model-based machine learning tool for generating key parameter ranges for test vectors for complex aerospace system models. The model will enable the Air Force to develop, test and certify new Unmanned Aircraft Systems (UAS) technology quickly, overcoming slow and costly traditional aircraft testing processes.
Agility Prime is an Air Force program seeking to accelerate the commercial market for advanced air mobility vehicles, like air taxis. QS-2 works closely with federal and commercial entities to advance Urban Air Mobility, helping clients evaluate safety designs and considerations for vehicle models and unmanned traffic management concepts, develops custom solutions for evaluating UAM fleet management operations, and is developing vertiport design techniques to assist in developing infrastructure to support UAM operations.
Quantitative Scientific Solutions has teamed on this effort with industry leader Crown Consulting Inc. (Crown) who is leading the project, as well as North Carolina State University. The vehicle model parameters are being designed and developed at QS-2 by Dr. Shawn Kimmel and Jeremiah Robertson, and led by Crown Science & Research team experts Dr. Karen Gundy-Burlet and Dr. Rubén Del Rosario with partner Dr. Tim Menzies of North Carolina State University.
QS-2’s Director of Engineering, Dr. Shawn Kimmel said, “This project is a significant step towards certification of autonomous systems in the National Airspace System”.