The study proposes a data assimilation approach to address imperfections in people flow measurement techniques. The method uses a fusion of measurement and simulation, applying these to agent-based simulation. This approach combines the advantages of both measurement and simulation, leading to a more accurate reflection of real people flow and richer data. The effectiveness of the proposed method is verified in a virtual environment and shows the potential of data assimilation to compensate for the three types of imperfections in people flow measurement techniques. The findings can serve as guidelines for supplementing sparse measurement data in physical environments.
Publication date: 19 Jan 2024
Project Page: https://arxiv.org/pdf/2401.09014.pdf
Paper: https://arxiv.org/pdf/2401.09014
