|Title:||Evaluation of Methods and Tools for Interactively Visualizing and Exploring Traffic Data||Language:||English||Authors:||Aslam, Arslan Muhammad||Qualification level:||Diploma||Advisor:||Gartner, Georg||Issue Date:||2020||Number of Pages:||107||Qualification level:||Diploma||Abstract:||
Increased traffic is becoming a growing problem in today’s cities and to enable efficient traffic management, decision makers need to be supported with valuable information. This requires functional visualizations that are capable of interactively exploring large amount of spatio-temporal traffic data and support identification of traffic congestion. The thesis evaluates methods and tools to visualize line based traffic data over the road network. The evaluated visualization concepts have been implemented in a web GIS traffic visualization prototype, developed using the visualization framework deck.gl. The dashboard based prototype incorporates a traffic attribute to measure traffic congestion (Travel Time Index), different visualization styles combining two visual variables and the ability for dynamic data exploration through data filtering, multiple temporal and spatial aggregates. These features are integrated in an interactively linked user interface allowing an overview of the data, as well as multidimensional traffic data exploration, to help in visual analytics tasks of domain experts. The developed prototype’s ability to spatially and temporally explore traffic congestion is demonstrated in the thesis. Additionally, the multiple interactive features are also evaluated through a user evaluation study with traffic experts and GIS professionals. The user study yielded positive results, which has increased confidence in the developed prototype and it’s capability to investigate traffic congestion. The combined use of two visual variables (color and width) for road based traffic visualization was specifically appreciated by the users. The developed prototype is presented as an example of a powerful and functionally capable traffic data visualization, which can be applicable to other cities as well.
|Keywords:||traffic visualization; traffic congestion; visual analytics; Travel Time Index; web-GIS||URI:||https://doi.org/10.34726/hss.2020.85823
|DOI:||10.34726/hss.2020.85823||Library ID:||AC16101452||Organisation:||E120 - Department für Geodäsie und Geoinformation||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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checked on May 26, 2021
checked on May 26, 2021
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