United States Department of Transportation
i
Rotorcraft Landing Sites Identification – Scaling and Generalization of the AI Model
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2022-06-01
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[PDF-10.62 MB]
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Corporate Contributors:Rutgers University. Center for Advanced Infrastructure and Transportation ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Federal Aviation Administration ; United States. Department of Transportation. Federal Highway Administration
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Edition:Final Report 03/1/2021 – 02/28/2022
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Abstract:The updated information about the location and type of landing sites is essential for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). However, the acquisition, verification, and regular updating of information about landing sites are not straightforward. The lack of current and correct information on helicopter landing sites is a risk factor in several accidents and rotorcraft incidents. The U.S. Helicopter Safety Team (USHST), of which the FAA is a key member, has identified and produced recommendations from their infrastructure working group to modernize and improve “the collection, dissemination, and accuracy of heliport/helipad landing sites” as a high priority to increase helicopter safety. In the last couple of years, the Rowan team has been developing an AI-based system to identify landing sites from satellite images. The project activities were performed in collaboration with the FAA. The developed AI algorithm accepts latitude/longitude values and search radius (in miles) from the user and performs a detailed search for any landing sites, helipads, or landing ports. The results returned to the user consist of satellite images marked with possible landing sites and corresponding latitude/longitude coordinates of the identified landing sites. The AI algorithm can also scan whole cities, towns, or extensive areas to locate and mark landing sites. The team has updated the FAA’s 5010 databases of helipads, heliports, and landing sites using the developed AI.
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