  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 and the principle of economy of scale that uses little
information in input to generate structures that are similar to those of public
transportation networks. 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 train, tram and subway networks, we find a noteworthy
degree of similarity in several of the studied cases between simulated and real
infrastructures. By tuning one parameter, our method can simulate a range of
different subway, tram and train 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.
