[1F3-OS-40a] OS-40

[1F3-OS-40a-02] Dynamic Origin-Destination Distribution Estimation with Extended LDA Model

〇Hideki Hayashi¹, Hirotaka Kaji², Kazushi Ikeda¹ (1. Nara Institute of Science and Technology, 2. Toyota Motor Corporation)

Keywords:Mobility, LDA, OD, Generative Model

Today, accurate forecasting of urban transportation demand is becoming increasingly important. Although large volumes of mobility data are required for such forecasting, privacy considerations often mean that only aggregated statistics are available. If the generative model of mobility data can be estimated from these statistics, it becomes possible to generate pseudo mobility data, which can be beneficial for transportation demand forecasting. In this study, we propose a method for estimating model parameters from statistical data under the assumption that mobility data are generated by the Latent Dirichlet Allocation (LDA). The effectiveness of the proposed method was demonstrated through experiments using real data from a bike-sharing system.