What question did this study set out to answer?

This survey aims to categorize and review conflict detection and resolution methods for Unmanned Aircraft Traffic Management systems, focusing on both classical and AI-based approaches.

December 11, 2024IEEE Transactions on Intelligent Transportation Systems

A Comprehensive Survey on Conflict Detection and Resolution in Unmanned Aircraft System Traffic Management

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This survey aims to categorize and review conflict detection and resolution methods for Unmanned Aircraft Traffic Management systems, focusing on both classical and AI-based approaches.
Comprehensive survey of literature on UAV conflict detection and resolution methods and their application in UTM systems.
Classification of methods into classical (non-learning) and learning-based (AI) approaches.
Examination of challenges and issues related to each method category.
Identified several classical methods that rely on predefined algorithms for conflict avoidance.
Outlined various AI-based methods, including machine learning and reinforcement learning, and their ability to enable UAVs to adapt and effectively resolve conflicts.
Discussed the application of these methods within Unmanned Aircraft Traffic Management services.

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Implication

Comprehensive survey identifies AI-based and classical methods for managing UAV conflicts in UTM, highlighting challenges.

Cite This Study

Hamissi et al. (2024) studied this question.

synapsesocial.com/papers/6a6225595aedc878c5f565f7 https://doi.org/10.1109/tits.2024.3509339

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A Comprehensive Survey on Conflict Detection and Resolution in Unmanned Aircraft System Traffic Management

Key Points

Discussion

Implication

Cite This Study

A Comprehensive Survey on Conflict Detection and Resolution in Unmanned Aircraft System Traffic Management

Key Points

Discussion

Implication

Cite This Study

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