Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation
We propose a framework for predicting the effects of mobility introduction measures using a human-flow digital twin. This digital twin incorporates a multi-agent simulator that can represent how visitors choose destinations depending on factors such as their current location and the attractiveness of spots. We extract data on how visitors selected destinations with respect to measured pre-intervention human-flow data, inter-spot distances, spot attractiveness, and travel volumes, and use these data to train each agent's decision model of this simulator. The trained decision model is a function that takes a visitor's current state and surrounding environmental information as input and outp...
| Authors | Chiharu Shima, Haruki Yonekura, Fukuharu Tanaka et al. |
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| Primary category | cs.MA |
| Published | 17 May 2026 |
| Last updated at source | 17 May 2026 |
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