Unmanned Aircraft Systems are increasingly used to monitor and sense our cities and the diffusion of UAS will require a Traffic Management System to coordinate UAS in the low-altitude airspace. In this paper we propose a collision avoidance strategy to be implemented in an Unmanned Aircraft System Traffic Management (UTM). The proposed strategy relies on a Cloud-based architecture that monitors and manages the low-altitude airspace, as well as coordinating the fleet of UAS. The strategy uses a Priority-based Model Predictive Control approach to define the optimal trajectory of the UAS, avoiding obstacles and other UAS with higher priority. The optimal trajectory is shared with other UAS to communicate the own motion track to be avoided by other UAS. The suggested method is implemented and tested in simulations with three UAS with conflicting trajectories. Preliminary results positively support the proposed approach.

A Cloud-based Vehicle Collision Avoidance Strategy for Unmanned Aircraft System Traffic Management (UTM) in Urban Areas / Primatesta, Stefano; Scanavino, Matteo; Lorenzini, Andrea; Polia, Francesco; Stabile, Enrico; Guglieri, Giorgio; Rizzo, Alessandro. - ELETTRONICO. - Proceedings of the 2020 IEEE International Workshop on Metrology for Aerospace:(2020), pp. 1-5. ((Intervento presentato al convegno 2020 IEEE International Workshop on Metrology for Aerospace [10.1109/MetroAeroSpace48742.2020.9160145].

A Cloud-based Vehicle Collision Avoidance Strategy for Unmanned Aircraft System Traffic Management (UTM) in Urban Areas

Stefano Primatesta;Matteo Scanavino;Giorgio Guglieri;Alessandro Rizzo
2020

Abstract

Unmanned Aircraft Systems are increasingly used to monitor and sense our cities and the diffusion of UAS will require a Traffic Management System to coordinate UAS in the low-altitude airspace. In this paper we propose a collision avoidance strategy to be implemented in an Unmanned Aircraft System Traffic Management (UTM). The proposed strategy relies on a Cloud-based architecture that monitors and manages the low-altitude airspace, as well as coordinating the fleet of UAS. The strategy uses a Priority-based Model Predictive Control approach to define the optimal trajectory of the UAS, avoiding obstacles and other UAS with higher priority. The optimal trajectory is shared with other UAS to communicate the own motion track to be avoided by other UAS. The suggested method is implemented and tested in simulations with three UAS with conflicting trajectories. Preliminary results positively support the proposed approach.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2837698