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TZVis: visual analysis of bicycle data for traffic zone division

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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.

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Acknowledgements

This work is partly supported by National Natural Science Foundation of China (No. 61972356), Zhejiang Provincial Natural Science Foundation of China (No. LY19F020026), National Natural Science Foundation of China (No. 61602409), Zhejiang Provincial Key Research and Development Program of China No. 2019C01009) and Fundamental Research Funds for the Provincial Universities of Zhejiang (No. RF-C2019001).

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Authors and Affiliations

  1. Zhejiang University of Technology, Hangzhou, China

    Guodao Sun, Baofeng Chang, Lin Zhu, Hao Wu & Ronghua Liang

  2. Hangzhou Comprehensive Transportations Information Center, Hangzhou, China

    Kai Zheng

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  1. Guodao Sun
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  2. Baofeng Chang
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  3. Lin Zhu
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  4. Hao Wu
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  5. Kai Zheng
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  6. Ronghua Liang
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Correspondence to Guodao Sun or Ronghua Liang.

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Sun, G., Chang, B., Zhu, L. et al. TZVis: visual analysis of bicycle data for traffic zone division. J Vis 22, 1193–1208 (2019). https://doi.org/10.1007/s12650-019-00600-6

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  • DOI: https://doi.org/10.1007/s12650-019-00600-6

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