Please use this identifier to cite or link to this item: http://dlib.scu.ac.ir/handle/Hannan/504303
Title: High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication
Authors: Jianqi Liu;Jiafu Wan;Dongyao Jia;Bi Zeng;Di Li;Ching-Hsien Hsu;Haibo Chen
Year: 2017
Publisher: IEEE
Abstract: With the increasing number of vehicle and traffic jams, urban traffic management is becoming a serious issue. In this article, we propose novel four-tier architecture for urban traffic management with the convergence of VANETs, 5G networks, software-defined networks, and mobile edge computing technologies. The proposed architecture provides better communication and more rapid responsive speed in a more distributed and dynamic manner. The practical case of rapid accident rescue can significantly shorten the rescue time. Key technologies with respect to vehicle localization, data pre-fetching, traffic lights control, and traffic prediction are also discussed. Obviously, the novel architecture shows noteworthy potential for alleviating traffic congestion and improving the efficiency of urban traffic management.
URI: http://dl.kums.ac.ir/handle/Hannan/504303
volume: 55
issue: 1
More Information: 34,
40
Appears in Collections:2017

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Title: High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication
Authors: Jianqi Liu;Jiafu Wan;Dongyao Jia;Bi Zeng;Di Li;Ching-Hsien Hsu;Haibo Chen
Year: 2017
Publisher: IEEE
Abstract: With the increasing number of vehicle and traffic jams, urban traffic management is becoming a serious issue. In this article, we propose novel four-tier architecture for urban traffic management with the convergence of VANETs, 5G networks, software-defined networks, and mobile edge computing technologies. The proposed architecture provides better communication and more rapid responsive speed in a more distributed and dynamic manner. The practical case of rapid accident rescue can significantly shorten the rescue time. Key technologies with respect to vehicle localization, data pre-fetching, traffic lights control, and traffic prediction are also discussed. Obviously, the novel architecture shows noteworthy potential for alleviating traffic congestion and improving the efficiency of urban traffic management.
URI: http://dl.kums.ac.ir/handle/Hannan/504303
volume: 55
issue: 1
More Information: 34,
40
Appears in Collections:2017

Files in This Item:
File Description SizeFormat 
7823335.pdf1.15 MBAdobe PDFThumbnail
Preview File
Title: High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication
Authors: Jianqi Liu;Jiafu Wan;Dongyao Jia;Bi Zeng;Di Li;Ching-Hsien Hsu;Haibo Chen
Year: 2017
Publisher: IEEE
Abstract: With the increasing number of vehicle and traffic jams, urban traffic management is becoming a serious issue. In this article, we propose novel four-tier architecture for urban traffic management with the convergence of VANETs, 5G networks, software-defined networks, and mobile edge computing technologies. The proposed architecture provides better communication and more rapid responsive speed in a more distributed and dynamic manner. The practical case of rapid accident rescue can significantly shorten the rescue time. Key technologies with respect to vehicle localization, data pre-fetching, traffic lights control, and traffic prediction are also discussed. Obviously, the novel architecture shows noteworthy potential for alleviating traffic congestion and improving the efficiency of urban traffic management.
URI: http://dl.kums.ac.ir/handle/Hannan/504303
volume: 55
issue: 1
More Information: 34,
40
Appears in Collections:2017

Files in This Item:
File Description SizeFormat 
7823335.pdf1.15 MBAdobe PDFThumbnail
Preview File