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Modeling the influence of restriction policies and perceived risk due to COVID-19 on daily activity scheduling

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  • Cortes Balcells, Cloe
  • Torres, Fabian
  • Krueger, Rico
  • Bierlaire, Michel

Abstract

This study develops an Activity-Based Model (ABM) framework to provide a deeper understanding of how activity restriction policies and perceived risks influence human mobility and, consequently, disease transmission. We propose three main contributions: (i) the Activity-Based Restriction Model (ABRM) systematically implements various activity restriction policies, such as closures, curfews, and distance-based limitations, (ii) we introduce a dynamic programming algorithm to address computational intractability in large-scale scenarios, significantly reducing computation time, (iii) we build a Risk Perception Latent Variable Model to simulate how perceived risks influence individual scheduling behavior. By embedding this model into the ABRM, we create the Activity-Based Risk Perception Restriction Model (ABR2M), which captures the dynamic interplay between risk perception and activity scheduling given activity-restriction policies. This integrated approach provides a detailed evaluation of individual schedules, offering valuable insights for the development of informed transportation policies.

Suggested Citation

  • Cortes Balcells, Cloe & Torres, Fabian & Krueger, Rico & Bierlaire, Michel, 2025. "Modeling the influence of restriction policies and perceived risk due to COVID-19 on daily activity scheduling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:transa:v:200:y:2025:i:c:s0965856425002320
    DOI: 10.1016/j.tra.2025.104604
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    References listed on IDEAS

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