首页|The visual analytics of big,open public transport data-a framework and pipeline for monitoring system performance in Greater Sydney
The visual analytics of big,open public transport data-a framework and pipeline for monitoring system performance in Greater Sydney
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NETL
NSTL
万方数据
维普
Many cities,countries and transport operators around the world are striving to design intelligent transport systems.These systems cap-ture the value of multisource and multiform data related to the functionality and use of transportation infrastructure to better sup-port human mobility,interests,economic activity and lifestyles.They aim to provide services that can enable transportation custo-mers and managers to be better informed and make safer and more efficient use of infrastructure.In developing principles,guidelines,methods and tools to enable synergistic work between humans and computer-generated informa-tion,the science of visual analytics continues to expand our under-standing of data through effective and interactive visual interfaces.In this paper,we describe an application of visual analytics related to the study of movement and transportation systems.This application documents the use of rapid,2D and 3D web visualisation and data analytics libraries and explores their potential added value to the analysis of big public transport performance data.A novel approach to displaying such data through a generalisable framework visualisa-tion system is demonstrated.This framework recalls over a year's worth of public transport performance data at a highly granular level in a fast,interactive browser-based environment.Greater Sydney,Australia forms a case study to highlight poten-tial uses of the visualisation of such large,passively-collected data sets as an applied research scenario.In this paper,we argue that such highly visual systems can add data-driven rigour to service planning and longer-term transport decision-making.Furthermore,they enable the sharing of quality of service statistics with various stakeholders and citizens and can showcase improvements in ser-vices before and after policy decisions.The paper concludes by making recommendations on the value of this approach in embed-ding these or similar web-based systems in transport planning practice,performance management,optimisation and understand-ing of customer experience.
WebGLvisual analyticspublic transportationtransport performancevisualisationopen databig data
Oliver Lock、Tomasz Bednarz、Christopher Pettit
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City Analytics Lab,Faculty of Built Environment,University of New South Wales,Sydney,Australia
Expanded Perception and Interaction Centre,Faculty of Art&Design,University of New South Wales,Sydney,Australia
NETL
NSTL
万方数据
维普
