Social Distancing with the Optimal Steps Model

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.

One-dimensional short-range nearest-neighbor interaction and its nonlinear diffusion limit

“…where ω 0 (s) is the limit of the initial data ω ∆s (s, 0), which exists by the BV -assumption (21). This is the weak formulation of the initial value problem (26) ∂…”

“…This diffusive term can be microscopically interpreted as particles trying to reach a desired density. The desired density is similar to the desired velocity, an important topic in pedestrian dynamics, see [1,19], gaining new focus in the context of social distancing [26], and cannot be calibrated in other macroscopic models, see [19].…”

Modeling and interactive simulation of measures against infection transmission

“…5 The original Vadere framework models walking behavior of people (agents) using various locomotion models that were calibrated and validated against empirical real-life observations. 26,27 Dynamic agent behavior is simulated in a 2D plane by means of the topography visualizer for various locomotion models.…”

Modelling airborne transmission of SARS-CoV-2 at a local scale

“…The locomotion model allows to simulate different distancing behaviours. Modelling physical distancing with the optimal steps model was demonstrated for a bottleneck scenario in [50]. However, we must adapt different parameters to obtain the right behaviour if we consider a queue under distancing regulations: The parameter pedPotentialPersonalSpace-Width, in the following denoted by p, allows to change the extent of an individual's personal space.…”