Songyang Yan

Causal Contrastive Learning with Data Augmentations for Imitation-Based Planning

Motion planning is a difficult task, especially when generating feasible future trajectories in complex and interactive scenarios. While recent advancements in imitation-based planning have shown significant progress, this approach often encounters causal confusion in dynamic traffic environments. T