Human Mobility Intelligence

Human Mobility Intelligence combines mobility data science, geospatial artificial intelligence, agent-based modeling, and behavioral simulation to understand how people move, conduct activities, and interact across space and time.

Overview

Our research develops computational representations of human mobility that connect observed movement with the activities, constraints, and social contexts that produce it. Rather than treating trajectories as isolated coordinates, we model people, places, schedules, transportation choices, and interactions as parts of a coupled human–spatial system.

Research Questions

• How can mobility models represent activities and motivations rather than movement alone?
• How can synthetic populations and observed data be combined without exposing individual records?
• How can mobility intelligence support policy evaluation across different communities and spatial scales?

Methods

• Spatiotemporal mobility analytics and GeoAI
• Agent-based and activity-based simulation
• Synthetic populations and patterns-of-life modeling
• Mobility prediction, validation, and uncertainty analysis

Applications

• Transportation and urban planning
• Public health and accessibility
• Disaster response and community resilience
• Responsible generation and use of mobility data

Selected Outputs

• HD-GEN: high-performance human mobility data generation
• Patterns-of-Life and GeoSocial simulation frameworks
• Human mobility prediction and benchmarking studies