Bibliographic Details
| Title: |
Research on UAV Conflict Detection and Resolution Based on Tensor Operation and Improved Differential Evolution Algorithm |
| Authors: |
Zhichong Zhou, Guhao Zhao, Yiru Jiang, Yarong Wu, Jiale Yang, Lingzhong Meng |
| Source: |
Aerospace, Vol 11, Iss 12, p 1008 (2024) |
| Publisher Information: |
MDPI AG, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Motor vehicles. Aeronautics. Astronautics |
| Subject Terms: |
unmanned aerial vehicles, flight conflict detection, tensor Hadamard product, prime factorization, differential evolution algorithm, conflict resolution, Motor vehicles. Aeronautics. Astronautics, TL1-4050 |
| More Details: |
With the widespread application of unmanned aerial vehicles (UAVs) in civilian and military fields, how to effectively detect and resolve conflicts of large-volume and high-density UAV flights in local airspace has become an important issue. This paper proposes a method for UAV conflict detection and resolution based on tensor operation and an improved differential algorithm. Firstly, the UAV protection zone model and airspace rasterization model are constructed, and the rapid detection of flight conflicts is achieved by using the properties of tensor Hadamard product operations and prime factorization. Then, for the detected conflicts, a hybrid improved differential evolution algorithm is used for resolution. This algorithm improves the solution speed and quality by using an adaptive mutation operator and introducing a redundant evaluation mechanism and a confidence-based selection strategy. Simulation results show that this method can quickly and accurately detect and resolve flight conflicts in high-density UAV scenarios, with high timeliness and conflict resolution capability. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2226-4310 |
| Relation: |
https://www.mdpi.com/2226-4310/11/12/1008; https://doaj.org/toc/2226-4310 |
| DOI: |
10.3390/aerospace11121008 |
| Access URL: |
https://doaj.org/article/12b428d9d4384e44b4002e21bc0b738c |
| Accession Number: |
edsdoj.12b428d9d4384e44b4002e21bc0b738c |
| Database: |
Directory of Open Access Journals |
