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Citywide Traffic Analysis Based on the Combination of Visual and Analytic Approaches

Liu, F., Andrienko, G. ORCID: 0000-0002-8574-6295, Andrienko, N. ORCID: 0000-0003-3313-1560, Chen, S., Janssens, D., Wets, G. and Theodoridis, Y. (2020). Citywide Traffic Analysis Based on the Combination of Visual and Analytic Approaches. Journal of Geovisualization and Spatial Analysis, 4(2), 15.. doi: 10.1007/s41651-020-00057-4


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.

Publication Type: Article
Additional Information: This is a post-peer-review, pre-copyedit version of an article published in Journal of Geovisualization and Spatial Analysis. The final authenticated version is available online at:
Publisher Keywords: visual analytical approaches, traffic conditions, travel patterns, congestion, GPS data
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
H Social Sciences > HE Transportation and Communications
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science > giCentre
Date available in CRO: 07 May 2021 11:26
Date deposited: 7 May 2021
Date of acceptance: 6 June 2020
Date of first online publication: 18 June 2020
Text - Accepted Version
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