Social Wayfinding-Inspired InFrasTructure(SWIIFT) for the Design of Public Spaces



Jacob Feldman


Mubbasir Kapadia 


Fred Roberts


Mathew Schartz


Karin Stromswold 


Graduate Students


Serena De Stefani


Sam Sohn









Project summary: 

In 2020, many public spaces were hastily redesigned to optimize pedestrian flow in order to minimize the spread of COVID-19. Unfortunately, conventional methods for simulating how people move through public spaces do not take into account social factors that affect how people actually navigate in the presence of other people (social wayfinding). For example, these methods do not incorporate how people adjust to avoid others’ personal space, navigate around slower-moving people, or follow instructions from other people. Even worse, existing simulations usually assume everybody has identical abilities, which is rarely true in real populations. The goal of this project is to develop a system for simulating the flow of people through public spaces, including social aspects of human navigation, and incorporating people with a variety of abilities and disabilities. These more realistic simulations will be used to develop novel metrics and protocols for evaluating public spaces, which more thoroughly reflect the rich social behavior of real people.

This project develops a new framework for modeling the flow of people through public spaces, called the Social Wayfinding-Inspired InFrasTructure (SWIIFT) design framework. The framework has three interlocking parts: human subjects experiments on human wayfinding, computational simulations of the flow of people through public spaces, and evaluation metrics for assessing design and re-design of real public spaces. In a series of experiments, human subjects will be immersed via Virtual Reality headsets into simulated spaces. These spaces will contain different numbers of simulated people, including people with variations in mobility (using wheelchairs, canes or walkers; pushing strollers; carrying heavy bags), sensory ability (e.g., visual impairments, hearing impairments), knowledge, and attention. Human subjects will receive different cues about which way to go, including visible pathways, signage, and verbal instructions. Data about the choices they make as they navigate through the virtual spaces will be incorporated into simulations, allowing us to develop realistic models of how people move through spaces under natural conditions. Finally, this framework will use these simulation models to evaluate potential modifications to real spaces, allowing potentially expensive changes to be accurately evaluated before they are carried out. The ultimate goal of this work is to enable public spaces to be made more efficient and more accessible for everyone, regardless of ability.



Potential human pathways though a simulated environment 

 Heatmap of human presence in a simulated environment  dome.png
 people_obstacle.png  Virtual environment used in human experiments
 Actual human pathways to avoid a person in VR experiments  paths.png


Funded by NSF


Jacob Feldman Research