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UAM Demand Capacity Modeling through Ensemble Learning (UDC-ModEL)
Completed
TRL 3 (started at 2, targeting 3)
Description
UAM operations are estimated in the hundreds to thousands of flights every day in each of their metropolitan market regions. Further, most of these flights are expected to employ electric propulsion vertical takeoff/landing aircraft (eVTOL). While eVTOLs offer many advantages over conventional gasoline fueled aircraft, huge strides are needed in battery or energy storage technologies to enable long duration flights. The immediate implication for this is that airborne eVTOLs may not have large reserves of energy to implement congestion mitigation procedures such as hold patterns. Further, current technology requires many hours to recharge the batteries on these aircraft, which implies that the UAM operators require accurate predictions of available airspace capacity to schedule their operations and manage their fleet’s energy resources. Given this situation, there is a need for accurate estimation of available capacity and how the prevalent demand can be balanced to take full advantage of this capacity, also known as demand capacity balancing (DCB). From another perspective, accurate DCB estimation offers the opportunity to evaluate which technological and operational enhancements best serve the prevalent and anticipated demand. The concept of DCB has been implemented within the commercial aviation world at some of the busiest airports across the world. However, those DCB approaches do not readily translate for the UAM paradigm. To address these needs and gaps, IAI proposes UAM Demand Capacity Modeling through Ensemble Learning (UDC-ModEL) to accurately and rapidly model DCB at UAM vertiports. As the name suggests, our technology leverages the latest advances in machine learning and artificial intelligence to erect a rapid estimation capability that is agnostic to the UAM market’s location or the eVTOL fleet mix used by a UAM operator. UDC-ModEL will be a valuable decision support tool for UAM operators and the proposed Providers of Services for UAM (PSUs).
Benefits
The ATM-X project, the UAM Sub-project, the AAM National Campaign, RVLT program and IASP program will directly benefit from UDC-ModEL. With UDC-ModEL, it will be possible to not only evaluate the performance of existing airspace conditions at a vertiport but also in comparing candidate enhancements to operating procedures and technologies under consideration by vertiports, PSUs and UAM operators. Also, UDC-ModEL will be valuable for design and development of eVTOL and other concepts to provide improved airspace capacity and throughput.
Aircraft manufacturers, PSUs and vertiport operators are customers for UDC-ModEL. Since UAM will serve both people and cargo movements, it is important to understand the subtleties of these two broad categories when operating the aircraft and the vertiports. UDC-ModEL will provide an agile platform to conduct what-if studies to quickly evaluate candidate options for the aforementioned customers.
Details
| Technology area | Flight Vehicle Systems > Aeroscience > Aeroacoustics |
| Program | Small Business Innovation Research/Small Business Tech Transfer (SBIR/STTR) |
| Lead organization | Intelligent Automation, Inc., Rockville, MD |
| Start date | 2021-05-19 |
| End date | 2021-11-19 |
Project contacts
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How to get involved
This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.
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