Conflict detection and resolution for unmanned aerial vehicles (UAVs) based on prime factorization

This paper presents a conflict detection and resolution model for unmanned aerial vehicles (UAVs) based on the principle of prime factorization. The goal is to achieve autonomous path planning and conflict management in a decentralized flight architecture. The model draws on the widely used prime factorization method in informatics and cryptography, applying the process of decomposing integers into prime products to UAV flight control. Based on the gridded airspace represented as a matrix, the process of integer decomposition into prime factors is utilized in UAV flight control, which possesses a certain degree of innovation. Through simulation experiments in complex air traffic environments, the model's effectiveness in identifying potential conflicts and dynamically adjusting flight altitude was validated. Results indicate that the model can ensure flight safety and efficiency in most cases and demonstrates good scalability, maintaining efficient operation even with a significant increase in the number of UAVs. This study provides a promising solution for decentralized UAV flight control, although it remains in the preliminary stages. Further research and optimization are expected to expand the scope of autonomous UAV flight. Future work will focus on improving algorithm efficiency, optimizing flight strategies, and conducting broader testing and validation in real-world environments.