4 papers · 1 filter
LSRE: Latent Semantic Rule Encoding for Real-Time Semantic Risk Detection in Autonomous Driving
Qian Cheng, Weitao Zhou, Cheng Jing +5
Real-world autonomous driving must adhere to complex human social rules that extend beyond legally codified traffic regulations. Many of these semantic constraints, such as yieldin…
Are All Data Necessary? Efficient Data Pruning for Large-scale Autonomous Driving Dataset via Trajectory Entropy Maximization
Zhaoyang Liu, Weitao Zhou, Junze Wen +4
Collecting large-scale naturalistic driving data is essential for training robust autonomous driving planners. However, real-world datasets often contain a substantial amount of re…
DTCCL: Disengagement-Triggered Contrastive Continual Learning for Autonomous Bus Planners
Yanding Yang, Weitao Zhou, Jinhai Wang +8
Autonomous buses run on fixed routes but must operate in open, dynamic urban environments. Disengagement events on these routes are often geographically concentrated and typically…
Dynamically Local-Enhancement Planner for Large-Scale Autonomous Driving
Nanshan Deng, Weitao Zhou, Bo Zhang +4
Current autonomous vehicles operate primarily within limited regions, but there is increasing demand for broader applications. However, as models scale, their limited capacity beco…