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Human-centered modeling framework of multiple interdependency in urban systems for simulation of post-disaster recovery processes

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Abstract

This paper presents a human-centered modeling framework of urban systems to capture various types of interdependency underlying urban sociotechnical and socioeconomic systems. The proposed framework consists of three major subsystems: civil life, manufacturing/service industry, and lifeline infrastructure. This framework classifies nine different types of interdependencies existing within and between these three subsystems. This paper also presents a computer simulation of the post-disaster recovery process of urban systems considering various interdependencies captured by the modeling framework. We adopt an agent-based model incorporating a network model for implementing the three subsystems as well as the various types of interdependencies. A sensitivity analysis was conducted based on the R4 framework of disaster resilience to verify and validate the simulation model. The simulation results were generally consistent with the predictions made by the R4 framework, suggesting that the model was implemented properly and can capture the multiple interdependencies behind the urban systems.

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Funding

This study was partly supported by Research Institute of Science and Technology for Society (RISTEX), Japan Science and Technology Agency (JST).

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Authors and Affiliations

  1. Department of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo, Japan

    T. Kanno, S. Koike & T. Suzuki

  2. Resilience Engineering Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan

    K. Furuta

Authors
  1. T. Kanno
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  2. S. Koike
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  3. T. Suzuki
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  4. K. Furuta
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Corresponding author

Correspondence to T. Kanno.

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This study is not involving human participants and/or animals.

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The authors declare that they have no conflict of interest.

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Kanno, T., Koike, S., Suzuki, T. et al. Human-centered modeling framework of multiple interdependency in urban systems for simulation of post-disaster recovery processes. Cogn Tech Work 21, 301–316 (2019). https://doi.org/10.1007/s10111-018-0510-2

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  • DOI: https://doi.org/10.1007/s10111-018-0510-2

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