A complex network analysis of macroscopic structure of taxi trips

Homayoun Hamedmoghadam-Rafati, Ingrida Steponavice, Mohsen Ramezani, Meead Saberi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

5 Citations (Scopus)


Despite the growing availability of big mobility data in cities, methodologies to extract meaningful information from them are still scarce. In this paper, we investigate taxi trips in New York City, develop a large-scale weighted and directed mobility network, and apply a macroscopic methodology to extract the spatial-temporal structure of urban mobility. We also present a new approach to study weighted networks of mobility in which links in the network have journey speed or travel time attribute in addition to commonly used link weights representing number of trips between pairs of nodes. We show that the structure of mobility network in a city when temporal characteristics and variations are taken into account exhibit different properties than what was previously observed. Results provide a better understanding of mobility characteristics in cities.

Original languageEnglish
Title of host publicationIFAC-PapersOnLine
Subtitle of host publication20th IFAC World Congress
EditorsDenis Dochain, Didier Henrion, Dimitri Peaucelle
Place of PublicationAmsterdam Netherlands
PublisherElsevier - International Federation of Automatic Control (IFAC)
Number of pages6
Publication statusPublished - 1 Jul 2017
EventInternational Federation of Automatic Control World Congress 2017 - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
Conference number: 20th

Publication series

PublisherElsevier - International Federation of Automatic Control (IFAC)
ISSN (Print)2405-8963


ConferenceInternational Federation of Automatic Control World Congress 2017
Abbreviated titleIFAC 2017
Internet address


  • Big Data
  • Parsimonious Modeling
  • Power Law
  • Taxi
  • Urban Mobility

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