High-Efficiency Urban Traffic Management in Context-Aware Computing and 5G Communication

Jianqi Liu, Jiafu Wan*, Dongyao Jia, Bi Zeng, Di Li, Ching Hsien Hsu, Haibo Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

124 Citations (Scopus)


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.

Original languageEnglish
Article number7823335
Pages (from-to)34-40
Number of pages7
JournalIEEE Communications Magazine
Issue number1
Publication statusPublished - Jan 2017
Externally publishedYes

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