SOURCE-LINKED INTELLIGENCE

SkyDrive: Learning to Drive in a New City from Aerial Traffic Monitoring

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Autonomous driving has made remarkable progress through imitation learning with massive human demonstration data. However, a trained planner often degrades severely when applied to a new environment zero-shot, because of domain shifts in traffic regulations, road layout and driving behaviors. Therefore, adapting a trajectory planner to a new city typically requires resource-demanding local data collection with a vehicle sensor suite. In this work, we show that driving behavior can be learned from a scalable and efficient alternative. We introduce \emph{SkyDrive}, a framework that utilizes dron

Read original source ↗ Open in workspace

recordType

paper

region

Global