Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/65559
Title: Visual analytics for massive urban public transport data
Authors: Zeng, Wei
Keywords: DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation
Issue Date: 2015
Source: Zeng, W. (2015). Visual analytics for massive urban public transport data. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: Public transport systems (PTSs) play an important role in modern cities. From the perspective of commuters, PTS provides shared and rapid transport services that are essential for the general public in a city. From the perspective of city management and urban planning, PTS has significant economical, social and environmental impacts to an entire city. Hence, studying PTS is highly beneficial to both individuals as well as a city as a whole, and it has long been a hot topic in transport research. However, many conventional transport researches have long been relying on simulation and survey data, making the results less of conviction. Thanks to recent advances in sensing technologies, such as RFID cards, laser scanners and GPS devices, movements acquisition has become convenient. Vast amount of urban public transport data has been collected automatically and pervasively, promoting more research fo- cus on analyzing and exploring public transport data when studying PTS. However, analyzing massive urban public transport data is a challenging task due to its high-complex, large-size, multi-mode and spatio-temporal characteristics. To get over these challenges, visual analytics show great potential as they can make the way of processing public transport data transparent: Visual analytics can provide interactive means for transport researchers to examine the actual processes of analyzing data instead of just the results. This thesis investigates advanced visualization technologies for analyzing and exploring mas- sive urban public transport data that consists of commuter RFID card data, transport network and transit schedule in Singapore. To address various analytical tasks raised by transport re- searchers, a family of novel visual analytics systems have been developed. Specifically, three aspects of high-level information, which are essential in transport modeling and analysis pro- cesses, have been extracted from the input dataset for visualization and exploration:• Interchange Pattern, which describes how moving objects redistribute when entering and passing through a junction node in a traffic network. A novel visual representation, namely the interchange circos diagram, has been proposed to present interchange pattern emerged from the public transport data. • Waypoints-Constrained OD Pattern, which restricts origin-destination (OD) pattern with commuter trajectories passing through user-specified entry and exit waypoints in a trans- port network. A novel unified visual representation, namely the waypoints-constrained OD view, has been proposed to explore waypoints-constrained OD pattern. • Mobility, which can be considered as the travel efficiencies of commuters through PTS. An integrated visualization with three modules: isochrone map view, isotime flow map view and OD-pair journey view, has been proposed to address a family of analytical tasks based on inputs from transport researchers.
URI: https://hdl.handle.net/10356/65559
DOI: 10.32657/10356/65559
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Theses

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