SUN Guodao, LI Si, CAO Dizhou, LIU Chunhui, JIANG Xiaorui, LIANG Ronghua. DiffusionInsighter: Visual Analysis of Traffic Diffusion Flow Patterns[J]. Chinese Journal of Electronics, 2018, 27(5): 942-950. DOI: 10.1049/cje.2017.12.008
Citation: SUN Guodao, LI Si, CAO Dizhou, LIU Chunhui, JIANG Xiaorui, LIANG Ronghua. DiffusionInsighter: Visual Analysis of Traffic Diffusion Flow Patterns[J]. Chinese Journal of Electronics, 2018, 27(5): 942-950. DOI: 10.1049/cje.2017.12.008

DiffusionInsighter: Visual Analysis of Traffic Diffusion Flow Patterns

  • Traffic jam has become a severe urban problem to most metropolises in the world. How to understand and resolve these traffic problems has become a global issue. In the new era of big data, visualization and analysis with traffic-related data are increasingly appreciated. This paper presents DiffusionInsighter, a web-based visual traffic analysis system, that allows users to explore the traffic flow and diffusion patterns with different spatial and temporal granularity. The DiffusionInsighter first applies a visual data cleaning and filtering component to remove dirty data and remain available ones for further analysis. A set of carefully designed interaction and visualization tools including geographical view, pixel map view, chord diagram and network diffusion view is proposed in the DiffusionInsighter to support level-of-detail exploration of diffusion patterns of the traffic flow. Different views are collaborated together and are integrated into geographic map. A series of real-life case studies are conducted using a large GPS trajectory dataset of taxis in Hangzhou.
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