CyberinfraV1, Main, Exploration, bibRecord, 000444

Parallelized Fusion on Multisensor Transportation Data: A Case Study in CyberITS

Identifieur interne : 000444 ( Main/Exploration ); précédent : 000443; suivant : 000445

Parallelized Fusion on Multisensor Transportation Data: A Case Study in CyberITS

Auteurs : YINGJIE XIA [République populaire de Chine] ; XIUMEI LI [République populaire de Chine] ; ZHENYU SHAN [République populaire de Chine]

Source :

International journal of intelligent systems [ 0884-8173 ] ; 2013.

RBID : Pascal:13-0251641

Descripteurs français

Pascal (Inist)
- Productivité, Type donnée, Capteur mesure, Traitement donnée, Système information, Architecture système, Conversion de données, Système réparti, Parallélisation, Fusion donnée, Haute performance, Temps réel, Capteur multiple, Consommation énergie, Economies d'énergie, Théorie Dempster Shafer, Autogénération mutuelle, Efficacité, Modélisation, Base donnée très grande, Théorie ensemble approximatif.
Wicri :
- topic : Productivité.

English descriptors

KwdEn :
- Bootstrapping, Data conversion, Data fusion, Data processing, Data type, Dempster Shafer theory, Distributed system, Efficiency, Energy consumption, Energy savings, High performance, Information system, Measurement sensor, Modeling, Multisensor, Parallelization, Productivity, Real time, Rough set theory, System architecture, Very large databases.

Abstract

With increasing requirements on traffic efficiency, environmental quality, energy efficiency, and economic productivity, intelligent transportation systems (ITS) research, which is centered on traffic state evaluation, meets two grand challenges. One is to process heterogeneous transportation data collected from different types of traffic sensors and the other is to reduce the high computation intensity for processing massive transportation data. To overcome both challenges, this paper proposes an approach using parallelized fusion on multisensor transportation data. Parallelized fusion is an embodied case of CyberITS framework, which is developed for the synthesis of cyberinfrastructure and ITS. The fusion functionality is shaped by a rough evidential fusion model (REFM) based on rough set and Dempster-Shafer evidence theories. The REFM consists of four components, which are sensor data input, bootstrapping rough conversion, hierarchical evidential fusion, and traffic state output. Their computation intensity is centered on conversion and fusion components, which can be optimized by the algorithm- and data-centric parallelization, respectively. Computational experiments for accuracy and efficiency demonstrate that parallelized fusion achieves a distributed, high-performance, and collaborative CyberITS implementation to provide accurate and real-time traffic state evaluation.

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<front><div type="abstract" xml:lang="en">With increasing requirements on traffic efficiency, environmental quality, energy efficiency, and economic productivity, intelligent transportation systems (ITS) research, which is centered on traffic state evaluation, meets two grand challenges. One is to process heterogeneous transportation data collected from different types of traffic sensors and the other is to reduce the high computation intensity for processing massive transportation data. To overcome both challenges, this paper proposes an approach using parallelized fusion on multisensor transportation data. Parallelized fusion is an embodied case of CyberITS framework, which is developed for the synthesis of cyberinfrastructure and ITS. The fusion functionality is shaped by a rough evidential fusion model (REFM) based on rough set and Dempster-Shafer evidence theories. The REFM consists of four components, which are sensor data input, bootstrapping rough conversion, hierarchical evidential fusion, and traffic state output. Their computation intensity is centered on conversion and fusion components, which can be optimized by the algorithm- and data-centric parallelization, respectively. Computational experiments for accuracy and efficiency demonstrate that parallelized fusion achieves a distributed, high-performance, and collaborative CyberITS implementation to provide accurate and real-time traffic state evaluation.</div>
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Parallelized Fusion on Multisensor Transportation Data: A Case Study in CyberITS

Parallelized Fusion on Multisensor Transportation Data: A Case Study in CyberITS

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri