The Unmanned Aerial Vehicles (UAVs) integration in the civil air traffic will contribute to the reduction of technical barriers related to safety and operational challenges associated with enabling routine UAV access to the civil airspace. While manned aircraft involve pilots and the Air Traffic Controller to take decisions, and follow their preassigned paths to avoid collisions with other aircraft, UAVs still need the definition of algorithms and rules. In this paper, a collision avoidance algorithm based on International Civil Aviation Organization (ICAO) rules to resolve possible conflicts among aircraft that are on a collision course while flying to their respective destinations is proposed. The proposed algorithm is based on the combination of collision prediction, speed optimization and inverse proportional navigation algorithms. Different strategies are activated on the basis of the UAV status and in particular on the evaluation of the risk level leading the UAV in a de-confliction or avoidance mode. Numerical simulations are presented to show the effectiveness of the proposed approach in the presence of many UAVs.

Distributed Collision Avoidance for Unmanned Aerial Vehicles Integration in the Civil Airspace

D'Amato E.
;
2018-01-01

Abstract

The Unmanned Aerial Vehicles (UAVs) integration in the civil air traffic will contribute to the reduction of technical barriers related to safety and operational challenges associated with enabling routine UAV access to the civil airspace. While manned aircraft involve pilots and the Air Traffic Controller to take decisions, and follow their preassigned paths to avoid collisions with other aircraft, UAVs still need the definition of algorithms and rules. In this paper, a collision avoidance algorithm based on International Civil Aviation Organization (ICAO) rules to resolve possible conflicts among aircraft that are on a collision course while flying to their respective destinations is proposed. The proposed algorithm is based on the combination of collision prediction, speed optimization and inverse proportional navigation algorithms. Different strategies are activated on the basis of the UAV status and in particular on the evaluation of the risk level leading the UAV in a de-confliction or avoidance mode. Numerical simulations are presented to show the effectiveness of the proposed approach in the presence of many UAVs.
2018
978-1-5386-1354-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/79019
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