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.
This SAI project is led by a team of investigators. Along with Pallab Mozumder, collaborators Nafisa Halim (Boston University) and Samiul Hasan (University of Central Florida) are co-leading research efforts. The focus of their SAI project is to improve understanding of emergent individual, social, and agency behaviors for evacuation traffic management during rapidly intensifying hurricanes (RIH). Extreme weather events (e.g., hurricanes, storm surges and flooding) threaten the status, sustainability and security of coastal communities. The drenching rains, gusty winds, and storm surges during a hurricane event force people to evacuate on short notice. Moreover, these events bring down power lines and trees, which in turn, disrupt critical infrastructure and utility services. Climate change is not only making hurricanes stronger, but also making them rapidly intensify and putting vulnerable populations at risk. In recent years, Atlantic hurricanes have shown unusual upward trends in rapid intensification (an increase of at least 35 miles/hour of windspeed in a 24-hour period) making critical infrastructure management more challenging during these extreme weather events. Concentrating on RIH, the project analyzes the dynamics of risk information processing and decision making to inform the design, development, improvisation, and overall evacuation management for critical transportation infrastructure. How infrastructure operators, emergency management personnel, and general public interact during coastal hazards, especially for evacuation during RIH, is critical for building resilient coastal communities. The insights from this project facilitate safer evacuations and help efficiently organize risk-averting behaviors during RIH.
This SAI EAGER project develops a multidisciplinary, data intensive and integrated framework to explore the pathways of adaptive infrastructure (transportation) management with RIH. The project integrates individual and agency level perspectives of evacuation during RIH. To understand emergency management challenges from infrastructures perspectives, the research team analyzes existing data of hurricane evacuation and mobility patterns available from transportation systems databases and social media. To gain further insights on these key challenges, the research team is conducting interviews with infrastructure and emergency management personnel and other stakeholders. The project develops analytical and scenario-based models to evaluate best practices, both short-term and long-term, for addressing emerging infrastructure and mobility management challenges. The research explores potential avenues for scaling-up best practices relating to improvisation (short-term) and adaptation (long-term) in an effort to develop more resilient infrastructure within coastal communities. The project offers an innovative, active learning environment and gives priority to the disadvantaged and underrepresented communities.
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.