用轻量变压器模型预测非管制空域飞机轨迹，提升通用航空安全
ASCENT: Transformer-Based Aircraft Trajectory Prediction in Non-Towered Terminal Airspace
- 基于变压器架构，融合3D坐标归一化与参数化输出
- 在两个数据集上优于现有方法，多模态预测误差更低
- 适合实时空管系统，尤其适用于高密度非管制机场
准确的飞行轨迹预测可提升非管制终端空域中通用航空的安全性，该区域交通密度高，事故风险大。本文提出ASCENT，一种轻量级基于Transformer的多模态3D飞机轨迹预测模型，集成领域感知的3D坐标归一化和参数化预测。ASCENT采用基于变压器的运动编码器和基于查询的解码器，能够以低延迟生成多样化的机动假设。在TrajAir和TartanAviation数据集上的实验表明，该模型优于先前基线，编码器有效捕捉运动动态，解码器与结构化飞机航迹模式对齐。消融研究证实了解码器设计、坐标系建模及参数化输出的贡献。结果表明，ASCENT是实现非管制终端空域实时飞机轨迹预测的有效方法。
原文摘要 · Abstract (English)
Accurate trajectory prediction can improve General Aviation safety in non-towered terminal airspace, where high traffic density increases accident risk. We present ASCENT, a lightweight transformer-based model for multi-modal 3D aircraft trajectory forecasting, which integrates domain-aware 3D coordinate normalization and parameterized predictions. ASCENT employs a transformer-based motion encoder and a query-based decoder, enabling the generation of diverse maneuver hypotheses with low latency. Experiments on the TrajAir and TartanAviation datasets demonstrate that our model outperforms prior baselines, as the encoder effectively captures motion dynamics and the decoder aligns with structured aircraft traffic patterns. Furthermore, ablation studies confirm the contributions of the decoder design, coordinate-frame modeling, and parameterized outputs. These results establish ASCENT as an effective approach for real-time aircraft trajectory prediction in non-towered terminal airspace.
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