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Title: Visualisation of traffic in space-time
Author: Tanaksaranond, G.
ISNI:       0000 0004 5363 5026
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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Road traffic congestion is the most persistent and debilitating problem in nearly all cities. Understanding congestion in space-time can greatly facilitate understanding of the beginning and evolution of congestion. Visualisation can be a tool to solve traffic congestion by getting insight into traffic data. This thesis focuses on developing visualisation techniques that can reveal space-time characteristics of traffic congestion, inclusive of how traffic congestion starts, disperses, and dissipates over the road network. Three main techniques are developed in this thesis, which include: wall map, isosurface, and constraint isosurface. The 3D wall map visualises the change of traffic and highlights congestion on each link. The 3D isosurface reveals sizes and shapes, and also the development of congestion. The constrained isosurface gives similar information to the isosurface, but locations of congestion are more localized. The three methods show how the origins and dispersion of congestion occurred. They also show different details of traffic data. A Graphic User Interface (GUI) was developed to allow users to interact with the traffic data and also to manipulate the visualisation to effectively support the identification of congested areas and relevant spatio-temporal information. The user-centred design approach was employed from the beginning of the GUI design process to ensure the ease of use. The massive amounts of traffic data are organised by data warehousing and by online analytical processing (OLAP) techniques, which improve multidimensional query response time. The system is implemented for link travel time data from Automatic Number Plate Recognition (ANPR). The combination of visualisation techniques with GUI and effective data management can help traffic managers to better understand how traffic congestion changes on the road network, and to uncover the solutions to congestion.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available