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Ko, Sungahn
IVADER: Interactive Visual Analysis and Data Exploration Research
Research Interests
  • Information visualization, visual analytics, human-computer interaction (HCI)

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A Visual Analytics System for Exploring, Monitoring, and Forecasting Road Traffic Congestion

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Title
A Visual Analytics System for Exploring, Monitoring, and Forecasting Road Traffic Congestion
Author
Lee, ChunggiKim, YeonjunJin, Seung MinKim, DongminMaciejewski, RossEbert, DavidKo, Sungahn
Issue Date
2019-06
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, pp.1 - 1
Abstract
We present an interactive visual analytics system that enables traffic congestion exploration, surveillance, and forecasting based on vehicle detector data. Through domain expert collaboration, we have extracted task requirements, incorporated the Long Short-Term Memory (LSTM) model for congestion forecasting, and designed a weighting method for detecting the causes of congestion and congestion propagation directions. Our visual analytics system is designed to enable users to explore congestion causes, directions, and severity. Congestion conditions of a city are visualized using a Volume-Speed Rivers (VSRivers) visualization that simultaneously presents traffic volumes and speeds. To evaluate our system, we report performance comparison results, wherein our model is more accurate than other forecasting algorithms. We demonstrate the usefulness of our system in the traffic management and congestion broadcasting domains through three case studies and domain expert feedback
URI
https://scholarworks.unist.ac.kr/handle/201301/26861
URL
https://ieeexplore.ieee.org/document/8735916
DOI
10.1109/tvcg.2019.2922597
ISSN
1077-2626
Appears in Collections:
ECE_Journal Papers
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