DocumentCode :
3712452
Title :
Hub Map: A new approach for visualizing traffic data sets with multi-attribute link data
Author :
Andrew Simmons;Iman Avazpour;Hai L. Vu;Rajesh Vasa
Author_Institution :
Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC, Australia
fYear :
2015
Firstpage :
219
Lastpage :
223
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.
Keywords :
"Visualization","Google","Vehicles","Detectors","Geospatial analysis","Semantics"
Publisher :
ieee
Conference_Titel :
Visual Languages and Human-Centric Computing (VL/HCC), 2015 IEEE Symposium on
Type :
conf
DOI :
10.1109/VLHCC.2015.7357220
Filename :
7357220
Link To Document :
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