A real-world traffic simulation can help better understand the need for infrastructure facilities in a region. Such simulations require digitized infrastructure information, well-represented people movement data, and efficient computing resources. Advances in computing resources and agent-based traffic simulators have made it possible to simulate real-world traffic conditions in a simulated environment. Digitized infrastructure datasets of roads, buildings, and other infrastructure facilities have enabled comprehensive visualization of infrastructure. However, the availability and accessibility of well-represented people’s mobility data are still part of some research. Additionally, due to resource limitations, traffic simulations are typically limited to geographic regions and use samples of traffic data rather than the entire population.This paper uses a novel mobility dataset, open Pseudo-PFLOW, which is a whole representation of the entire population of Japan, for a full-scale traffic modeling of Chiba prefecture. We used Multi-Agent Traffic Simulation (MATSim) tool, as an agent-based simulator. This has previously proven efficient for simulating large scenarios. The main research question focuses on improving agent trajectory data from the Pseudo-PFLOW dataset by agent-based modeling and validating the effectiveness of MATSim on network congestion and resource requirements of full-scale simulations.