TRACE: Trajectory Recovery with State Propagation Diffusion for Urban Mobility

1. 1Collect sparse GPS trajectory data
2. 2Apply state propagation diffusion to recover missing location points
3. 3Use TRACE to generate dense and continuous trajectories
4. 4Evaluate the performance of TRACE using metrics such as trajectory accuracy and completeness

Data scientists and AI engineers working on urban mobility projects can benefit from this research to improve the accuracy of location-based services, while product managers can utilize the insights to inform smart city applications

💡 TRACE can effectively recover dense and continuous GPS trajectories from sparse and unevenly distributed location points, enhancing the accuracy of location-based services

📍 Recovering dense GPS trajectories from sparse data with TRACE 💡