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This project aims to develop and test a “digital twin” (a realistic virtual copy) of an Urban Air Mobility system, such as air taxis operating in a city, to support safer and faster operational decisions. Using a simulated city environment of Montréal and realistic flight scenarios, the project will model key elements such as vehicle routes, traffic rules, takeoff/landing sites, and disruptions (weather, delays, or congestion). It will then integrate prediction and conflict-avoidance capabilities so the system can anticipate risky situations and recommend practical actions (for example, rerouting or holding at a waypoint). The expected benefits are improved safety and reliability, better traffic coordination, and clear guidance on what level of model detail is needed to support time-constrained decisions, helping accelerate the future deployment of Urban Air Mobility services.
Lokman Sboui
Tunisia Polytechnic School, University of Carthage
Engineering
Aerospace; Artificial Intelligence; Transportation (excluding aerospace)
École de technologie supérieure
Globalink Research Award
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.