SOURCE-LINKED INTELLIGENCE
Protocol before progress: leakage-aware evaluation of AIS trajectory prediction
Reported gains in vessel-trajectory prediction from Automatic Identification System (AIS) data are credited to new architectures, but the evaluation protocol is rarely measured as a source of error reduction. We build a leakage-aware protocol with vessel-, time- and region-disjoint splits and apply it to two corpora with different traffic: 31 days of Danish national AIS traffic and 30 days of US Gulf coast traffic off Houston and Galveston. On both, we audit TrAISformer, GATransformer, and controlled AISFormer-inspired reconstructions. Three protocol effects appear in both corpora. First, TrAI
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T07:54:45.000Z
First collected: 2026-09-23T04:21:13.910Z. This is not the publication date.