SAI: Modeling Equitable and Accessible Public Spaces

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.Substantial resources have been spent (re)designing America’s public transportation hubs to make them more accessible and easier to use, but people still find many transportation hubs hard to navigate. This is especially true for the one in four Americans who have mobility, sensory or cognitive impairments. Part of the difficulty stems from the failure to understand how social factors affect the way people with differing abilities interact with one another as they navigate different environments. Using virtual reality (VR) simulations of public transportation hubs, this project examines how people who have impairments or are temporarily encumbered navigate around physical objects and other people. It also considers how nondisabled people navigate around people who are disabled or encumbered, and how announcements and signs change the way diverse people travel through transportation hubs. These findings are used to create more realistic computer models of how people navigate crowded spaces, and to test what factors make public spaces more efficient and usable. Public transportation hubs are the primary focus because improving the usability of public transportation expands the educational, social, health and occupational opportunities that are available to all Americans. Improving the usability of public transportation hubs also helps to decrease America’s reliance on private transportation.This project is organized around three interlocking parts. One uses virtual reality (VR) to explore the navigational choices of people who have varying mobility and perceptual abilities. A second uses computational simulations of the navigational choices and flow of diverse people. The third part develops evaluation metrics for assessing the (re)design of real public spaces that take into consideration the variability in people and their navigational choices. A series of experiments on human wayfinding uses VR to embed human participants in simulated public transportation hubs. Unlike traditional navigation studies, these experiments focus on how human wayfinding is affected by the presence of other people. The VR experiments examine how people navigate environments that are populated by simulated others with varying mobility. They also consider how people respond when placed in situations that negatively impact their ability to navigate certain spaces, identify potential routes, or perceive instructions. The VR experiments also examine how those who use mobility aids navigate virtual environments that are populated with virtual people. This project aims to increase the usability of public spaces and transportation hubs for everyone, regardless of ability, thereby expanding educational, social, health and occupational opportunities for all.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Mathematical and Physical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.