<div>With the growing demand of air traffic, it becomes more important and critical than ever to develop advanced techniques to control and monitor air traffic in terms of safety and efficiency. Especially, trajectory prediction can play a significant role on the improvement of the safety and efficiency because predicted trajectory information is used for air traffic management such as conflict detection and resolution, sequencing and scheduling. </div><div><div>In this work, we propose a new framework by integrating</div><div>the two methods, called hybrid data-driven and physics-based trajectory prediction. The proposed algorithm is applied to real air traffic surveillance data to demonstrate its performance.</div></div>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/14517123 |
| Date | 30 April 2021 |
| Creators | Hansoo Kim (10727661) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/HYBRID_DATA-DRIVEN_AND_PHYSICS-BASED_FLIGHT_TRAJECTORY_PREDICTION_IN_TERMINAL_AIRSPACE/14517123 |
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