Abstract: As cities grow more dense, it will be of increasing importance to understand how the structure of urban road networks influences factors such as traffic flows. This project intends to develop a modeling framework to study the effective geometry of flows in spatial networks using tools from Riemannian geometry, which we then hope to apply to travel patterns in urban transportation systems. We use data on the shape of fastest driving routes in Manhattan to guide our inquiry and inform our understanding of the geometrical properties of these networks. Through this analysis we seek to infer a Riemannian metric which can characterize network flows and provide insight about congestion patterns in cities.
Video:
Live Poster Session:
Thursday, July 29th 1:15-2:30pm EDT