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| PREVIOUS CODE | UGOD 6100A |
|---|---|
| DESCRIPTION | This course examines human travel behaviors and mobility patterns across spatial and temporal dimensions, with a strong emphasis on the complex interactions between individual behavior and the urban environment. The course offers an interdisciplinary introduction to building AI-driven agent frameworks to understand, model, and simulate human mobility, and explore how urban environment, socio-economic factors, and other constraints shape individual and collective mobility patterns. Through theoretical frameworks, advanced analytical methods, and empirical tools (e.g., GPS tracking, mobile data), the course decodes how humans adapt their spatio-temporal travel behavior to evolving urban landscapes. Case studies on commuting efficiency, activity scheduling, accessibility disparities, and disaster resilience, and emerging trends such as shared mobility systems and virtual spaces will be covered. Through hands-on modeling and industry-linked case studies, students will learn to build and evaluate AI-agent systems for human mobility and urban studies. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6539) | Tu 06:00PM - 08:50PM | Rm 103, E1 | LI, Qiumeng | 15 | 15 | 0 | 0 |