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《电子学报(英文)》 2018-05
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Diffusion Insighter:Visual Analysis of Traffic Diffusion Flow Patterns

SUN Guodao;LI Si;CAO Dizhou;LIU Chunhui;JIANG Xiaorui;LIANG Ronghua;College of Information Engineering,Zhejiang University of Techonology;Department of Computer Science and Mathematics,Aston University;  
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 DiffusionI nsighter, 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 DiffusionI nsighter 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 DiffusionI nsighter 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 tra jectory dataset of taxis in Hangzhou.
【Fund】: supported by the National Natural Science Foundation of China(No.61602409);; Zhejiang Provincial NSFC(No.LR14F020002);; joint project Data-Driven Intelligent Transportation between China and Europe announced by the Ministry of Science and Technology of China(No.SQ2013ZOC200020);; the Open Projects Program of Key Laboratory of Ministry of Public Security based on Zhejiang Police College(No.2016DSJSYS003)
【CateGory Index】: U491
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