Hub Map: A new approach for visualizing traffic data sets with multi-attribute link data

Andrew Simmons, Iman Avazpour, Hai L. Vu, Rajesh Vasa

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

1 Citation (Scopus)

Abstract

Visualizing road traffic datasets involves representing junctions, their links, and the attributes of those links. Current traffic visualization techniques are not sufficient for professional traffic engineers, as they are limited in the number of attributes that can be represented. This paper proposes a new approach to visualize multiple attributes on graph edges without compromising their visibility. In particular, we introduce a parameterized connector symbol that increases the number of attributes that can be displayed on graph edges. We demonstrate that our approach can significantly increase the number of traffic parameters that can be displayed compared to existing traffic visualizations.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2015
Subtitle of host publication18 - 22 October, 2015 Atlanta, USA
EditorsZhen Li, Claudia Ermel, Scott D. Fleming
Place of PublicationPiscataway, NJ
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages219-223
Number of pages5
ISBN (Electronic)9781467374576, 9781467374569
DOIs
Publication statusPublished - 14 Dec 2015
Externally publishedYes
EventIEEE Symposium on Visual Languages and Human-Centric Computing 2015 - Atlanta, United States of America
Duration: 18 Oct 201522 Oct 2015
https://ieeexplore.ieee.org/xpl/conhome/7347691/proceeding (Proceedings)

Conference

ConferenceIEEE Symposium on Visual Languages and Human-Centric Computing 2015
Abbreviated titleVL/HCC 2015
CountryUnited States of America
CityAtlanta
Period18/10/1522/10/15
Internet address

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