QuteVis: Visually Studying Transportation Patterns Using Multisketch Query of Joint Traffic Situations

Shamal Al-Dohuki, Ye Zhao, Farah Kamw, Jing Yang, Xinyue Ye, Wei Chen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

QuteVis uses multisketch query and visualization to discover specific times and days in history with specified joint traffic patterns at different city locations. Users can use touch input devices to define, edit, and modify multiple sketches on a city map. A set of visualizations and interactions is provided to help users browse and compare retrieved traffic situations and discover potential influential factors. QuteVis is built upon a transport database that integrates heterogeneous data sources with an optimized spatial indexing and weighted similarity computation. An evaluation with real-world data and domain experts demonstrates that QuteVis is useful in urban transportation applications in modern cities.

Original languageEnglish (US)
Article number8691491
Pages (from-to)35-48
Number of pages14
JournalIEEE Computer Graphics and Applications
Volume41
Issue number2
DOIs
StatePublished - Mar 1 2021

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

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