RouteVis: Quantitative Visual Analytics of Various Factors to Understand Route Choice Preferences

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dc.contributor.authorLv, Chengen_US
dc.contributor.authorZhang, Huijieen_US
dc.contributor.authorLin, Yimingen_US
dc.contributor.authorDong, Jialuen_US
dc.contributor.authorTian, Liangen_US
dc.contributor.editorAigner, Wolfgangen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorBujack, Roxanaen_US
dc.date.accessioned2024-05-21T08:18:27Z
dc.date.available2024-05-21T08:18:27Z
dc.date.issued2024
dc.description.abstractAnalyzing the preference of route choice not only facilitates the understanding of individuals' decision-making behavior, but also provides valuable information for improving traffic management strategies. As the layout of the road network, the variability of individual preferences and the spatial distribution of origins and destinations all play a role in route choice, it is a great challenge to reveal the interplay of such numerous complex factors. In this paper, we propose RouteVis, an interactive visual analytics system that enables traffic analysts to gain insight into what factors drive individuals to choose a specific route. To uncover the relationship between route choice and influencing factors, we design a quantitative analytical framework that supports analysts in conducting closed-loop analysis of various factors, i.e., data preprocessing, route identification, and the quantification of influence and contribution. Furthermore, given the multidimensional and spatio-temporal characteristics of the analysis results, we customize a set of coordinated views and visual designs to provide an intuitive presentation of the factors affecting people's travels, thus freeing analysts from tedious repetitive tasks and significantly enhancing work efficiency. Two typical usage scenarios and expert feedback on the system's functionality demonstrate that RouteVis can greatly enhance the capabilities of understanding the travel status.en_US
dc.description.number3
dc.description.sectionheadersGeospatial Data and Optimization
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15091
dc.identifier.issn1467-8659
dc.identifier.pages12 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15091
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15091
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Human-centered computing->Visual analytics; Geospatial Data; Information visualization
dc.subjectHuman centered computing
dc.subjectVisual analytics
dc.subjectGeospatial Data
dc.subjectInformation visualization
dc.titleRouteVis: Quantitative Visual Analytics of Various Factors to Understand Route Choice Preferencesen_US
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