Projects

This project aims to develop an optimization–artificial intelligence (AI) integrated framework for travel demand forecasting in autonomous driving environments. As autonomous and conventional vehicles are expected to coexist for a prolonged period, the study focuses on modeling household-level travel behavior and activity patterns using an advanced activity-based modeling framework. The research integrates optimization methods and AI techniques to better capture changes in travel demand, vehicle usage, and network performance under various autonomous vehicle adoption scenarios. In addition, the project explores practical applications such as a household travel planner and peer-to-peer vehicle sharing matching service based on the developed model. The outcomes are expected to contribute to next-generation transportation demand forecasting, mobility service design, and evidence-based transportation policy in the era of autonomous mobility.