Revealing the similarity between urban transportation networks and optimal transport-based infrastructures


Designing and optimizing the structure of urban transportation networks is a challenging task. In this study, we propose a method inspired by optimal transport theory to reproduce the optimal structure of public transportation networks, that uses little information in input. Contrarily to standard approaches, it does not assume any initial backbone network infrastructure, but rather extracts this directly from a continuous space using only a few origin and destination points. Analyzing a set of urban rail, tram and subway networks, we find a high degree of similarity between simulated and real infrastructures. By tuning one parameter, our method can simulate a range of different networks that can be further used to suggest possible improvements in terms of relevant transportation properties. Outputs of our algorithm provide naturally a principled quantitative measure of similarity between two networks that can be used to automatize the selection of similar simulated networks.

Daniela Leite
Daniela Leite
PhD student

My PhD project is at the intersection between Math and Physics. In particular, my research focuses on trying to understand the dynamical behavior and properties of routing optimization networks.

Caterina De Bacco
Caterina De Bacco
CyberValley Research Group Leader

My research focuses on understanding, optimizing and predicting relations between the microscopic and macroscopic properties of complex large-scale interacting systems.