Towards Universal Urban Patterns-of-Life Simulation
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866908798607687680 |
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| author | Reia, Sandro M. de Arruda, Henrique F. Ruan, Shiyang Anderson, Taylor Kavak, Hamdi Pfoser, Dieter |
| author_facet | Reia, Sandro M. de Arruda, Henrique F. Ruan, Shiyang Anderson, Taylor Kavak, Hamdi Pfoser, Dieter |
| contents | Understanding urban mobility requires models that capture how people interact with and navigate the built environment. We present a scalable, generalizable agent-based framework in which daily schedules emerge from the interplay between mandatory (e.g., work, school) and flexible (e.g., errands, food, leisure) activities, driven by evolving individual needs. The results of our model are validated against empirical patterns from the 2017 U.S. National Household Travel Survey, including activity distributions, origin-destination flows, and trip-chain length distributions. We introduce a normalized similarity metric to quantify agreement between simulated and empirical patterns. Most cities achieve scores above 0.80, demonstrating strong alignment without the need for city-specific calibration. The model scales efficiently to over 20 million agents, enabling full-population simulations of large metropolitan areas. This combination of universality and scalability enables scenario analysis for infrastructure stress testing, disaster recovery, innovation diffusion, and disease spread in urban systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_22099 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Towards Universal Urban Patterns-of-Life Simulation Reia, Sandro M. de Arruda, Henrique F. Ruan, Shiyang Anderson, Taylor Kavak, Hamdi Pfoser, Dieter Physics and Society Understanding urban mobility requires models that capture how people interact with and navigate the built environment. We present a scalable, generalizable agent-based framework in which daily schedules emerge from the interplay between mandatory (e.g., work, school) and flexible (e.g., errands, food, leisure) activities, driven by evolving individual needs. The results of our model are validated against empirical patterns from the 2017 U.S. National Household Travel Survey, including activity distributions, origin-destination flows, and trip-chain length distributions. We introduce a normalized similarity metric to quantify agreement between simulated and empirical patterns. Most cities achieve scores above 0.80, demonstrating strong alignment without the need for city-specific calibration. The model scales efficiently to over 20 million agents, enabling full-population simulations of large metropolitan areas. This combination of universality and scalability enables scenario analysis for infrastructure stress testing, disaster recovery, innovation diffusion, and disease spread in urban systems. |
| title | Towards Universal Urban Patterns-of-Life Simulation |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2601.22099 |