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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/462846 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832561611540267008 |
|---|---|
| author | Yingjie Xia Jia Hu Michael D. Fontaine |
| author_facet | Yingjie Xia Jia Hu Michael D. Fontaine |
| author_sort | Yingjie Xia |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-072e951c85ab4459982ff1db77e88a28 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-072e951c85ab4459982ff1db77e88a282025-02-03T01:24:35ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/462846462846A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber InfrastructureYingjie Xia0Jia Hu1Michael D. Fontaine2Hangzhou Institute of Service Engineering, Hangzhou Normal University, 222 Wenyi Road, Hangzhou 310012, ChinaDepartment of Civil and Environmental Engineering, University of Virginia, 351 McCormick Road, Charlottesville, VA 22903, USADepartment of Civil and Environmental Engineering, University of Virginia, 351 McCormick Road, Charlottesville, VA 22903, USATraffic 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.http://dx.doi.org/10.1155/2013/462846 |
| spellingShingle | Yingjie Xia Jia Hu Michael D. Fontaine A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure The Scientific World Journal |
| title | A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure |
| title_full | A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure |
| title_fullStr | A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure |
| title_full_unstemmed | A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure |
| title_short | A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure |
| title_sort | cyber its framework for massive traffic data analysis using cyber infrastructure |
| url | http://dx.doi.org/10.1155/2013/462846 |
| work_keys_str_mv | AT yingjiexia acyberitsframeworkformassivetrafficdataanalysisusingcyberinfrastructure AT jiahu acyberitsframeworkformassivetrafficdataanalysisusingcyberinfrastructure AT michaeldfontaine acyberitsframeworkformassivetrafficdataanalysisusingcyberinfrastructure AT yingjiexia cyberitsframeworkformassivetrafficdataanalysisusingcyberinfrastructure AT jiahu cyberitsframeworkformassivetrafficdataanalysisusingcyberinfrastructure AT michaeldfontaine cyberitsframeworkformassivetrafficdataanalysisusingcyberinfrastructure |