A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.
Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This rese...
| Publicado en: | Scientific World Journal pp. 462846 - 462847 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104164986&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104164986 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104164986 104164986 NLM23766690 2012242047 10.1155/2013/462846 NLM23766690 PMC3671550 104164986 ppf: 462846 ppct: 1 formats: tig: atl: A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure. aug: au: Xia, Yingjie Hu, Jia Fontaine, Michael D affil: Hangzhou Institute of Service Engineering, Hangzhou Normal University, 222 Wenyi Road, Hangzhou 310012, China ; Department of Civil and Environmental Engineering, University of Virginia, 351 McCormick Road, Charlottesville, VA 22903, USA. sug: subj: Algorithms Computer Communication Networks Signal Processing, Computer Assisted Software Information Retrieval Methods ab: Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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