TrajFM: A Vehicle Trajectory Foundation Model for Region and Task Transferability

Understand

Vehicle trajectories provide valuable movement information that supports various downstream tasks and powers real-world applications.

• A desirable trajectory learning model should transfer between different regions and tasks without retraining, thus improving computational efficiency and effectiveness with limited training data.
• However, a model's ability to transfer across regions is limited by the unique spatial features and POI arrangements of each region, which are closely linked to vehicle movement patterns and difficult to generalize.
• Additionally, achieving task transferability is challenging due to the differing generation schemes required for various tasks.