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Erschienen in: Journal of Visualization 6/2019

10.09.2019 | Regular Paper

TZVis: visual analysis of bicycle data for traffic zone division

verfasst von: Guodao Sun, Baofeng Chang, Lin Zhu, Hao Wu, Kai Zheng, Ronghua Liang

Erschienen in: Journal of Visualization | Ausgabe 6/2019

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Abstract

Traffic zone is a geographical unit which is proposed to reduce the complexity of traffic control and management systems in modern urban road networks. Traffic zone could be generated by different division approaches (e.g., rule-based approaches, data-driven approaches), which may lead to different diverse division results and characteristics. The traditional division approaches usually rely on human experience or static constraints (e.g., political boundaries or natural environment) while neglecting the traveling pattern among different regions. Data-driven approaches are also utilized in recent years; however, domain knowledge and rules are not well integrated and represented in such systems. This paper proposes a new approach that both combines patterns that is hidden in the data and user-defined rules. It not only fully employs the traffic hot spots and traveling patterns among different regions, but also considers the realistic constraints such as road network. We also design TZVis, a visual analysis system that fully integrates with the division approach. The system allows users to generate multiple traffic zone division schemes under different requirements, analyze the schemes in multiple views and select an optimal traffic zone scheme. It provides a map overview to show the traffic zone division result, a matrix view to show the traffic relationship of zones, a parallel coordinates plot for displaying the specific traffic records, a LineUp view to display all the division results and a radar chart to show the features of each zones. We further test our division approach and demonstrate the usefulness of our system based on the shared bicycle dataset.

Graphic abstract

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Metadaten
Titel
TZVis: visual analysis of bicycle data for traffic zone division
verfasst von
Guodao Sun
Baofeng Chang
Lin Zhu
Hao Wu
Kai Zheng
Ronghua Liang
Publikationsdatum
10.09.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Visualization / Ausgabe 6/2019
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI
https://doi.org/10.1007/s12650-019-00600-6

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