SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning
This paper presents SD-RouteFusion, a deployable end-to-end ego-trajectory prediction method that fuses a front-facing camera, vehicle kinematics, and a navigation route derived from a Standard Definition (SD) map. Unlike approaches that rely on High Definition (HD) map geometry, SD-RouteFusion aligns the learning objective with scalable and production-ready SD-map route inputs, enabling route-aware prediction without requiring HD-map infrastructure. First, we demonstrate that SD-map route prior provides a powerful long-horizon semantic prior. Through a comprehensive study on a large-scale rea
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- PossiblePossibly related (embedding) · 47%autowarefoundation/auto_e2e →
- LinkedLinked via arxiv author · 85%Sviatoslav Voloshyn →
“SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning”
- LinkedLinked via arxiv author · 85%Bruno K. W. Martens →
“SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning”
- LinkedLinked via arxiv author · 85%Wangxin Liu →
“SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning”
- LinkedLinked via arxiv author · 85%Jakob Vinkås →
“SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning”
- LinkedLinked via arxiv author · 85%Junsheng Fu →
“SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning”
- PossiblePossibly related (embedding) · 51%autowarefoundation/autoware_vision_pilot →