Objective: To discuss the design requirements of digital twin (DT) for urban air mobility (UAM) operation monitoring system according to the findings from the development of a Mixed Reality (MR)-based digital twin (DT) demonstrator.
Background: UAM vehicles will fly within and around urban areas in the near future.
Since the UAM vehicles will fly above the urban airspace, proactive awareness of safety-related urban configurations is important. DT is a promising tool to plan, monitor, and assess collision probability with building obstacles and other air vehicles.
The MR technology is considered a good means of live 3D graphics for users and an application of DT. Applying the contemporary MR technology to a DT for UAM operations and assessing the DT functions are meant to consider UAM monitoring system design alternatives.
Method: Applying the systems engineering process, the author elicited five design requirements of the DT prototype for the UAM operation monitoring purpose. The author's team conducted indoor drone flights around a building miniature and downloaded the coordinates of drone flight trajectories. The team generated virtual 3D graphics of the drone and miniature in the MR application to simulate UAM flight operations in an urban area. The developed application demonstrated simple UAM flights visualizing a building obstacle, planned/actual/optimal flight paths, and no-fly zones. The A-Star algorithm determined and rapidly updated the recommended optimal flight path while the drone significantly deviated from the planned path. The author assessed the demonstrator design to see if the design met the requirements.
Results: The concept demonstrator satisfied four requirements of five regarding the DT functions for effective interaction with users.
Conclusion: The developed concept demonstrator designs may provide insights into the DT design directions of accurate planning, modeling, simulating, monitoring, and assessing UAM operations.
Application: The MR application will be an effective modeling and simulation tool to plan and monitor UAM operations and assess how the UAM vehicle searches for the optimal path avoiding building obstacles from the third-person view.