Trajectory Representation

Trajectory representation focuses on efficiently and effectively encoding movement data into a format suitable for various downstream tasks, such as navigation, traffic prediction, and human motion analysis. Current research emphasizes developing sophisticated models, including graph-based and transformer architectures, that capture both micro-level details (individual points and movements) and macro-level semantics (road networks, shared travel patterns, and behavioral context) within trajectories. These advancements improve the accuracy and efficiency of trajectory-based applications across diverse fields, from autonomous driving and robotics to urban planning and human behavior understanding. The development of explainable and robust representations, particularly those handling noisy or incomplete data, remains a key focus.