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The road to direction: Assessing the impact of road asymmetry on street network small-worldness

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Small-world networks have proven to be optimal navigational structures, by insuring an adequate balance between local and global network efficiency. In the particular case of road networks, small-world- oriented research has led to widely diverging results, depending on modelling procedures: while traditional, geometric, road-based models fail to observe small-world properties in road networks, a new street-based modelling approach has obtained opposite results, by observing small-world properties for both named-based and angularity-based street graphs. These results are however hampered by the fact that street-based modelling has so far overlooked road asymmetry. Given this, the present research aims at evaluating the impact of road asymmetry on street network "small-worldness", by comparing symmetric and asymmetric street graphs by means of a structural indicator recently developed in brain network analysis. Results show that taking into account road asymmetry better highlights not only the small-world nature of street networks, but also the exceptional structure of name-based (odonymic) street topologies.

Original languageEnglish
Title of host publicationSpatial Cognition IX - International Conference, Spatial Cognition 2014, Proceedings
Number of pages16
Publication year1 Jan 2014
ISBN (print)9783319112145
Publication statusPublished - 1 Jan 2014
Externally publishedYes
EventInternational Conference on Spatial Cognition IX, Spatial Cognition 2014 - Bremen, Germany
Duration: 15 Sep 201419 Sep 2014


ConferenceInternational Conference on Spatial Cognition IX, Spatial Cognition 2014
SponsorSFB/TR 8 Spatial Cognition, Spatial Intelligence and Learning Center, Transregional Collaborative Research Center
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8684 LNAI

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