4 papers
SF-LIFE: A Large-Scale Simulated Movement Dataset for the San Francisco Bay Area
Chanuka Algama, Taylor Anderson, Henrique Ferraz de Arruda +14
We introduce SF-LIFE, a large-scale simulated movement dataset designed to accelerate research in transportation, mobility, and machine learning. The dataset contains 3,024,000,000…
Towards Universal Urban Patterns-of-Life Simulation
Sandro M. Reia, Henrique F. de Arruda, Shiyang Ruan +3
Understanding urban mobility requires models that capture how people interact with and navigate the built environment. We present a scalable, generalizable agent-based framework in…
Extracting the U.S. building types from OpenStreetMap data
Henrique F. de Arruda, Sandro M. Reia, Shiyang Ruan +4
Building type information is crucial for population estimation, traffic planning, urban planning, and emergency response applications. Although essential, such data is often not re…
Function and form of U.S. cities
Sandro M. Reia, Taylor Anderson, Henrique F. Arruda +4
The relationship between urban form and function is a complex challenge that can be examined from multiple perspectives. In this study, we propose a method to characterize the urba…