Social Distancing with the Optimal Steps Model

Authors

  • Christina Maria Mayr Munich University of Applied Sciences, Department of Computer Science and Mathematics, Munich, Germany and Technical University Munich, Department of Informatics, Garching, Germany https://orcid.org/0000-0003-1686-3460
  • Gerta Köster Munich University of Applied Sciences, Department of Computer Science and Mathematics, Munich, Germany https://orcid.org/0000-0002-3369-6206

DOI:

https://doi.org/10.17815/CD.2021.116

Keywords:

optimal steps model (OSM), social distancing, bottleneck, parameter adaption, locomotion modeling, Vadere simulation framework

Abstract

With the Covid-19 pandemic, an urgent need has arisen to simulate social distancing. The Optimal Steps Model (OSM) is a pedestrian locomotion model that operationalizes an individual's need for personal space. We present new parameter values for personal space in the OSM to simulate social distancing in the pedestrian dynamics simulator Vadere. Our approach is pragmatic. We consider two use cases: in the first, we demand that a set social distance must never be violated. In the second the social distance can be violated temporarily for less than 10s. For each use case we conduct simulation studies in a typical bottleneck scenario and measure contact times, that is, violations of the social distance rule.
We conduct regression analysis to assess how the parameter choice depends on the desired social distance and the corridor width.
We find that evacuation time increases linearly with the width of the repulsion potential, which is an analogy to physics modeling the strength of the need for personal space. The evacuation time decreases linearly with larger corridor width. The influence of the corridor width on the evacuation time is smaller than the influence of the range of the repulsion, that is, the need for personal space. If the repulsion is too strong, we observe clogging effects.  
Our regression formulas enable Vadere users to conduct their own studies without understanding the intricacies of the OSM implementation and without extensive parameter adjustment.

Author Biographies

Christina Maria Mayr, Munich University of Applied Sciences, Department of Computer Science and Mathematics, Munich, Germany and Technical University Munich, Department of Informatics, Garching, Germany

Department of Computer Science and Mathematics

Gerta Köster, Munich University of Applied Sciences, Department of Computer Science and Mathematics, Munich, Germany

Department of Computer Science and Mathematics

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Published

17.12.2021

How to Cite

Mayr, C. M., & Köster, G. (2021). Social Distancing with the Optimal Steps Model. Collective Dynamics, 6, 1–24. https://doi.org/10.17815/CD.2021.116

Issue

Section

Pedestrian and Evacuation Dynamics 2021