Computational Cities: Designing and Modeling Smart and Safe Cities
Principal Investigator: Daniel Aliaga
This project addresses the growing desire to create geometrical models that design better, smarter, safer, and more efficient cities. Cities are inherently very complex to model because they are simultaneously dense and large, spanning from a few to hundreds of square kilometers, and because their underlying structure is influenced by a very large number of hard-to quantify variables including land policies, economic behavior, transportation infrastructure, governmental plans, and population changes. In this work, we blur the boundary between behavioral modeling and geometrical modeling of urban spaces. Within computer graphics and visualization research focuses on producing complex and visually appealing 3D geometrical models from images and/or LIDAR, while urban behavioral modeling focuses on accurate urban dynamics, predictive behaviors, and behaviorally-validated simulations using socio-economic data, for example. We are creating concurrent behavioral and geometrical simulations which significantly benefit the design, editing, and prediction of large-scale 3D city models. Coupled with human behavioral simulations, we strive to make the city itself more liveable and safer as well. The result is the ability to generate, in a few minutes, 3D city models that resemble existing locations, to simulate urban behaviors not previously possible, to predict and visualize the outcome of urban policies and regulations, to design cities that best conform to meteorological aspects, and to consider the urban ecosystem during the design phase.
Other PIs: Bedrich Benes