Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34719
Title: Citywide Traffic Analysis Based on the Combination of Visual and Analytic Approaches
Authors: LIU, Feng 
Andrienko, Gennady
Andrienko, Natalia
JANSSENS, Davy 
WETS, Geert 
Theodoridis, Yannis
Chen, Siming
Issue Date: 2020
Publisher: SPRINGERNATURE
Source: JOURNAL OF GEOVISUALIZATION AND SPATIAL ANALYSIS, 4 (2) (Art N° 15)
Abstract: A method for citywide traffic analysis is introduced based on the combination of visual and analytical approaches. Large volumes of GPS data collected from urban vehicles are utilized. In the method, a traffic condition map is constructed, composed of five different layers featuring traffic conditions, road linkage, travel patterns, congestion zones, and traffic flows, respectively. Based on the map, specific transport situations surrounding the congested areas are examined and ways of reducing congestion are suggested. The method is evaluated in the aggregated metropolitan area of Athens and Piraeus in Greece, and the potential and the effectiveness of this technique in analysing traffic are demonstrated. With more and more urban vehicles being equipped with GPS devices, the method can be easily transferable to other regions, paving the way for the adoption of the approach for an up-to-date, spatial-temporal sensitive, visual and analytic method for traffic monitoring that supports the establishment of a more sustainable urban transportation system.
Notes: Liu, F (corresponding author), Hasselt Univ, Transportat Res Inst IMOB, Wetenschapspk 5,Bus 6, B-3590 Diepenbeek, Belgium.
Feng.liu@uhasselt.be; gennady.andrienko@iais.fraunhofer.de;
Natalia.andrienko@iais.fraunhofer.de; Siming.Chen@iais.fraunhofer.de;
davy.janssens@uhasselt.be; geert.wets@uhasselt.be;
ytheodoridis@gmail.com
Keywords: Visual analytical approaches; Traffic conditions; Travel patterns;;Congestion; GPS data
Document URI: http://hdl.handle.net/1942/34719
ISSN: 2509-8810
e-ISSN: 2509-8829
DOI: 10.1007/s41651-020-00057-4
ISI #: WOS:000670273100001
Category: A1
Type: Journal Contribution
Validations: vabb 2023
Appears in Collections:Research publications

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