4D trajectory lightweight prediction algorithm based on knowledge distillation technique
The proposed method effectively balances high-precision modeling of spatiotemporal dependencies with lightweight deployment requirements, enabling real-time air-traffic monitoring and early warning on standard CPUs and embedded devices. This framework offers a scalable solution for enhancing the operational safety and efficiency of modern air-traffic control systems.
Authors
- Weizhen Tang (ORCID: https://orcid.org/0009-0004-4925-712X)
- Weiliang Xie (ORCID: https://orcid.org/0009-0008-2542-8050)
- Zhihui Huang
- Jiyan Dai (ORCID: https://orcid.org/0000-0002-7720-8032)
- Boyang Hao
Institutions
- Civil Aviation Flight University of China (CN)
Publication Details
- Journal
- Frontiers in Neurorobotics
- Published
- 2025-08-22
- DOI
- https://doi.org/10.3389/fnbot.2025.1643919
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Civil Aviation Administration of China