Using Interactive Space-Time Cube Visualisation for Pattern Mining in Bicycle Trajectories and Traffic-Related Parameters

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type 01 Jan 2023Embargo end date: 01 Apr 2023 Switzerland, Germany Publisher:Zenodo

Authors: Keler, Andreas; Ludwig, Sylvia; Zuo, Chenyu;

doi: 10.5281/zenodo.7839558 , 10.3929/ethz-b-000616657 , 10.5281/zenodo.7839557

handle: 20.500.11850/616657

Using Interactive Space-Time Cube Visualisation for Pattern Mining in Bicycle Trajectories and Traffic-Related Parameters

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Abstract

This work focuses on the visualisation of bicycle trajectories at an urban junction in Munich, Germany, using a Space-Time cube (STC) approach. The trajectories are obtained from a traffic observation using computer-vision-based approaches and pre-processed for analysis. A GUI implementation in MATLAB is introduced for evaluating the usefulness of the STC technique for transport planning and engineering purposes, with a focus on evaluating traffic safety. The visual patterns are evaluated by experts based on the quality of five interactive components of the implemented STC GUI.

ISBN:https://zenodo.org/communities/gisruk2023

Zenodo

Countries

Switzerland, Germany

Related Organizations

Technical University of Munich
Germany
Augsburg University of Applied Sciences
Germany
Universität Augsburg
Germany
TECHNISCHE UNIVERSITAET MUENCHEN
Germany
Technische Universität München

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Keywords

Data processing, Data processing; Data visualisation; Space-time cube; Traffic analysis; Bicycle trajectories, Bicycle trajectories, Traffic analysis, data processing, data visualisation, space-time cube, traffic analysis, bicycle trajectories, ddc:910, Data visualisation, Space-time cube

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