# Extracting the multimodal fingerprint of urban transportation networks

arXiv: https://arxiv.org/abs/2006.03435 · HTML: https://mlsanity.com/paper/2006.03435/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [Convolutional Learning on Multigraphs](https://mlsanity.com/paper/2209.11354/) (2022)

## Abstract (arXiv)

Urban mobility increasingly relies on multimodality, combining the use of bicycle paths, streets, and rail networks. These different modes of transportation are well described by multiplex networks. Here we propose the overlap census method which extracts a multimodal profile from a city's multiplex transportation network. We apply this method to 15 cities, identify clusters of cities with similar profiles, and link this feature to the level of sustainable mobility of each cluster. Our work highlights the importance of evaluating all the transportation systems of a city together to adequately identify and compare its potential for sustainable, multimodal mobility.