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UTM CITY Dubai- Visualisation and traffic management of unmanned traffic

Unmanned traffic in cities is expected to be the most profitable stage of drone usage (including drones that have remote human surveillance or a human pilot as backup). This will require new systems for unmanned/urban traffic management (UTM), that can operate with a higher level of autonomy/automation.

Current ATM systems require one controller per 5-15 flights, which is seen as unviable for UTM (operations will become too expensive). The purpose of UTM is to manage drone traffic safely and efficiently beyond line of sight. UTM manages current and planned traffic, airspace restrictions and contingencies. For cities, combined missions in shared airspace, especially with destination hotspots (e.g. airports, hotels, logistics hubs), can cause interactions between missions (i.e. adverse effects, such as congestion, inefficiency, risk of separation infringements). UTM manages and minimizes these adverse effects. This requires interactivity between mission management (in particular route planning) and UTM.

The purpose of the project is to design, prototype, and test concepts for Unmanned Traffic Management (UTM) for Dubai City in an interactive visualization and traffic simulation. The goals of the project are (1) to visualize in 3D unmanned air traffic (delivery drones) for Dubai City. Moreover, goal (2) is to define an operational concept for unmanned traffic and (3) to use it to define optimal routes for parcel delivery drones.

The project is managed by LIU in close collaboration with University of Sharjah, Saab, LFV and Dubai Aviation Engineering Projects (DAEP). The project is funded by VINNOVA.

Contact Persons:

  • Prof. Jonas Lundberg

Project Areas:

  • Human-AI/Automation Joint Control

Relevant Publications:

  • Human-in-the-loop AI: Requirements on future (unified) air traffic management systems
  • Routing of Unmanned Aerial Vehicles: State of the Art

Interesting URLs:

  • Human Automation Collaboration for Air Traffic Management

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