Trust-Based Collision Avoidance for Unmanned Aircraft Systems

The rapid expansion of Unmanned Aircraft (UA) usage has increased the need for reliable collision avoidance systems. This paper presents a trust-based, sensor-free collision avoidance system for UAs, leveraging the Drone Remote Identification Protocol (DRIP) to establish trust between aircraft. The proposed system uses a geometric-based cooperative avoidance method to optimize efficiency and a fail-safe repulsion avoidance mechanism for enhanced safety. The proposed system’s effectiveness is evaluated through a series of simulations and real-world tests, focusing on metrics such as safety, flight distance, flight time, and acceleration requirements. The results are promising, indicating that the trust-based approach may successfully balance efficiency and safety, providing insights into potential use cases for DRIP.

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Publication Details

Published
2024-11-28
DOI
https://doi.org/10.1109/incas63820.2024.10798560
Primary Topic
Air Traffic Management and Optimization
Type
article
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Trust-Based Collision Avoidance for Unmanned Aircraft Systems

Anastasia Lemetti, Mariusz Wzorek, Andrei Gurtov, Zelong Wang et al.
Air Traffic Management and Optimization
article

Trust-Based Collision Avoidance for Unmanned Aircraft Systems

Anastasia Lemetti, Mariusz Wzorek, Andrei Gurtov, Zelong Wang, Ernst Larsson-Kapp, Ville Kniivilä
article en

Abstract

The rapid expansion of Unmanned Aircraft (UA) usage has increased the need for reliable collision avoidance systems. This paper presents a trust-based, sensor-free collision avoidance system for UAs, leveraging the Drone Remote Identification Protocol (DRIP) to establish trust between aircraft. The proposed system uses a geometric-based cooperative avoidance method to optimize efficiency and a fail-safe repulsion avoidance mechanism for enhanced safety. The proposed system’s effectiveness is evaluated through a series of simulations and real-world tests, focusing on metrics such as safety, flight distance, flight time, and acceleration requirements. The results are promising, indicating that the trust-based approach may successfully balance efficiency and safety, providing insights into potential use cases for DRIP.

Linköping University (SE)
Openalex Percentile: Top 62%
Air Traffic Management and Optimization
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