This project aims to develop Scaper, an agent-based Dynamic Discrete Choice Model (DDCM) for simulating urban travel behavior at the population scale. The model captures multi-dimensional decision-making processes of individuals, including temporal dynamics, activity participation, and travel choices, within a unified framework. It is designed to support urban transportation policy evaluation and planning. Due to the need to simulate entire urban populations and resolve complex dynamic decisions, the model entails substantial computational demands. Using data from Helsinki, a single full-scale simulation currently requires over 100 hours on conventional computing resources. We therefore seek access to high-performance supercomputing resources to significantly improve computational efficiency, enable large-scale simulations, and support extensive scenario analysis. The main supervisor for this project is Anders Karlström, and the co-supervisor is Qain Wang. Both supervisors are affiliated with the KTH Department of Urban Planning and Environment.