SCC-PG: The Prospects for Artificial Intelligence in Urban Planning (NSF, 2021-2022): This project is a partnership between Virginia Tech, the American Planning Association (APA), and Arlington County, Virginia’s Departments of Community Planning, Housing and Development (DCPHD Planning Division) and Technology Services (DTS). As part of this planning grant, the partnership will survey members of the APA and conduct feasibility analysis workshops and focus group sessions with DCPHD. The objective is to assess a broad range of tasks performed by County planners and determine which of these have the highest likelihood of being assisted and improved by AI technologies. This includes county-level responsibilities for comprehensive planning, land use, infrastructure, environment, housing, parks, and transportation. This project expects that each of these areas has the potential for more advanced data and analytical capabilities. The approach partners researchers, planning professionals, and community members will focus on the explainability and transparency of AI-based planning activities. This relates to the equitable deployment of AI methods and will also address concerns about trust in the use of data and analytical processes.

EAGER: SAI: SmarTrail: An Infrastructure Services Framework for Sustainable Trail Management (NSF, 2021-2023): We are examining the potential to employ smartphones and other digital technologies in an information system to match long distance hikers’ needs with conservation objectives in protected areas. Our work blends digital information flows from textual analysis of digital communications (Instagram, Reddit, other social media platforms, and web-based trail logs) with interviews of resource managers, and surveys of long-distance hikers to explore the spatial, social, psychological, and cultural dimensions of trail protection and use. We draw from the fields of recreation ecology, human-computer interaction, social psychology, and public policy to mitigate visitor impacts and improve visitor experiences in protected areas.

Collaborative Research: CRISP Type2: Coordinated, Behaviorally-Aware Recovery for Transportation and Power Disruptions (NSF, 2017-2022). Our research seeks to develop joint recovery strategies from power and transportation infrastructure disruptions caused by hurricanes and other natural disasters. We aim specifically to incorporate the processing of information by individuals and behavioral adaptation in response to this information to better align infrastructure priorities with user needs to return households to productivity. Our research draws on a combination of social media, official utility and transport information, and activity surveys to develop behavioral models and infrastructure outage models that feed a coordinated, behaviorally-aware power and transportation recovery model using optimization and agent-based modeling. Our interdisciplinary team spans computer science, infrastructure engineering, behavioral studies, and agent-based modeling.

RAPID: Distancing & Digital Information in the Face of COVID-19 (NSF, 2020-2022): Our research project investigates risk perceptions, risk preferences, stated behavior, and actual behavior change in response to digital information during the COVID-19 crisis. As large numbers of people cut off spatial ties and limit their mobility in the COVID-19 pandemic, the demand for digital media has increased, yet this media coverage differs widely in quality, credibility, and timeliness across sources. To undertake the analysis, we are blending a multi-wave (2020-2022) national-level survey of residents in five US metropolitan areas with cluster and sentiment analysis of digital media coverage. Our team includes experts in social psychology, risk, and public policy.