SOURCE-LINKED INTELLIGENCE
DESCENT: Directed Edge Scene Encoding for Airport Surface Movement Prediction
Advanced automation is a key technology for enhancing the safety of ground operations amidst the increasing density of commercial air traffic. While motion forecasting is a well-studied task in autonomous driving, its application to airport surface movements remains underexplored. To enable efficient and accurate prediction in this domain, we propose DESCENT, a transformer-based architecture designed to handle heterogeneous dynamics and strict topological constraints. Our approach features a Potential Reachable Set (PRS) context sampling mechanism that adaptively collects airfield environment
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T16:49:50.000Z
First collected: 2026-09-21T09:11:58.312Z. This is not the publication date.