Applying real-time virtual reality and artificial intelligence for risk-based safety assessment of autonomous operations in a shared airspace

The objective of the research project that is the subject of this proposal is to simulate autonomous flight for the purpose of risk-based safety assessment using machine learning applications. Simulation methodologies are developed and implemented for the purpose of extracting data from real-time, publicly-accessible sources to create a virtual environment that represents actual airspaces including air traffic, weather, terrain obstacles and navigation aids. A simulated model of an autonomous aircraft can be flown in the virtual environment in order to study the risks associated with flying un-crewed aircraft in a shared airspace. Multiple scenarios can be developed and flown in a safe environment to help us better understand and mitigate the risks of new technologies. Artificial intelligence tools are used to help identify patterns in the complex interactions that characterize the aerospace eco-system of the future. The industrial partner in this project will be able to use the results of the research to better align their business model with the users of artificial intelligence in the context of autonomous aircraft operations.

Faculty Supervisor:

Catharine Marsden

Student:

Nicolas Vincent-Boulay;Angelina Cui

Partner:

Marinvent

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

Royal Military College of Canada

Program:

Accelerate

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