Often times, trajectories such as walking humans or driving cars are snapped to a road network for simplification and aggregation purposes. Public transportation also operates along a predefined network. The contextualization of this movement data can be used to expose and analyze temporal patterns in traffic flows.
The frequency of occurence is a common attribute to visualize on a road network. However, other data attributes such as the speed, delays, or gas consumption are also available for a deeper analysis.
Hence, visualizing multiple temporally dependent attributes along a road network to draw insights from urban movement data remains a challenging, but equally promising task.
- Evaluate and compare existing approaches for road network visualizations
- Develop a novel interactive, visual analysis technique to visualize and explore multiple data attribubes along a road network
- Compare your technique to other existing approaches
- Interest in spatiotemporal data analysis
- Basic knowledge about information visualization, data mining and geographic information systems
- Scope: Bachelor / Master
- 3 Months Project, 3 / 6 Months Thesis
- Start: immediately
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- T-Watcher: A New Visual Analytic System for Effective Traffic Surveillance. J. Pu et al.. IEEE 14th International Conference on Mobile Data Management (2013). DOI: 10.1109/MDM.2013.23
- A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data. W. Chen, Z. Huang, F. Wu, M. Zhu, H. Guan, & R. Maciejewski. IEEE Trans Vis Comput Graph. (2018). DOI: 10.1109/TVCG.2017.2758362
- Interactive Visualization of Traffic Dynamics Based on Trajectory Data.G. A. M. Gomes, E. Santos and C. A. Vidal. 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (2017). DOI: 10.1007/s10462-019-09736-1