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This research aims to evaluate conflict detection and resolution methods for UAV autonomy, with a focus on decentralized systems.

December 19, 2025Open Access

Conflict Detection, Resolution, and Collision Avoidance for Decentralized UAV Autonomy: Classical Methods and AI Integration

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Survey reviews UAV autonomy and safety outcomes from collision avoidance and decentralized automation, highlighting trust and adaptability.

This research aims to evaluate conflict detection and resolution methods for UAV autonomy, with a focus on decentralized systems.
Survey of classical methods and AI techniques in UAV conflict detection and resolution.
Analysis of noncooperative airspace users and its impact on UAV trajectory safety.
Examination of requirements for trust, transparency, and interpretability in automated UAV systems.
Identified limitations of classical rule-based approaches in UAV conflict resolution.
Highlighted the potential of machine learning to enhance adaptability in collision avoidance systems.
Discussed the evolving needs for trust and transparency in UAV autonomy settings.

d’Apolito et al. (2025) studied this question.

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Survey reviews UAV autonomy and safety outcomes from collision avoidance and decentralized automation, highlighting trust and adaptability.