An LLM-driven estimation framework for estimating regional travel structures based on spatiotemporal multi-modal travel data

Key Points

• An estimation framework effectively models regional travel structures using spatiotemporal data.
• Key evidence reveals enhancements in accuracy when integrating diverse travel data types—both spatial and temporal.
• Analysis utilizing multi-modal travel data reflects a comprehensive approach to estimate structures objectively.
• Findings indicate that such frameworks may enable more efficient travel planning and management, supporting better resource allocation.