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Journal of Advanced Transportation
Volume 2018, Article ID 3156137, 17 pages
https://doi.org/10.1155/2018/3156137
Research Article

Studying the Topology of Transportation Systems through Complex Networks: Handle with Care

1Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid, Spain
2Faculdade de Ciências e Tecnologia, Departamento de Engenharia Electrotécnica, Universidade Nova de Lisboa, 2829-516 Lisboa, Portugal
3National Key Laboratory of CNS/ATM, School of Electronic and Information Engineering, Beihang University, 100191 Beijing, China
4National Engineering Laboratory for Integrated Transportation Big Data Center, 100191 Beijing, China
5Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, 100083 Beijing, China

Correspondence should be addressed to Xiaoqian Sun; nc.ude.aaub@qxnus

Received 11 June 2018; Accepted 8 August 2018; Published 19 August 2018

Academic Editor: Samiul Hasan

Copyright © 2018 Massimiliano Zanin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The introduction of complex network concepts in the study of transportation systems has supposed a paradigm shift and has allowed understanding different transport phenomena as the emergent result of the interactions between the elements composing them. In spite of several notable achievements, lurking pitfalls are undermining our understanding of the topological characteristics of transportation systems. In this study, we analyse four of the most common ones, specifically related to the assessment of the scale-freeness of networks, the interpretation and comparison of topological metrics, the definition of a node ranking, and the analysis of the resilience against random failures and targeted attacks. For each topic we present the problem from both a theoretical and operational perspective, for then reviewing how it has been tackled in the literature and finally proposing a set of solutions. We further use six real-world transportation networks as case studies and discuss the implications of these four pitfalls in their analysis. We present some future lines of work that are stemming from these pitfalls and that will allow a deeper understanding of transportation systems from a complex network perspective.