A traffic hotline discovery method over cloud of things using big taxi GPS data. (3rd June 2016)

• Record Type: Journal Article
• Authors: Xu, Xiaolong; Dou, Wanchun; Zhang, Xuyun; Hu, Chunhua; Chen, Jinjun
• Other Names: Ranjan Rajiv guestEditor.; Wang Lizhe guestEditor.; Jayaraman Prem Prakash guestEditor.; Mitra Karan guestEditor.; Georgakopoulos Dimitrios guestEditor.
• Is Part Of: Software, practice & experience. Volume 47:Number 3(2017)
• Page Start: 361
• Page End: 377
• Publication Date: 2016-06-03
• Subjects: traffic hotline discovery -- big taxi GPS data -- transportation planning -- CoT; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2412
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: Traffic hotline discovery is necessary for rational and scientific urban transportation planning in the new living quarters and economic zones. Cloud of Things (CoT) is a newly emerging concept, involving with two advanced technologies, that is, Cloud Computing and Internet of Things (IoT). CoT provides promising opportunities for traffic hotline discovery. However, it is still a challenge to discover the traffic hotlines over CoT. In view of this challenge, a hotline discovery method over CoT by using big taxi GPS data is proposed in this paper. Specifically, a traffic hotline discovery principle is presented to provide a reference standard for the generalized traffic spots that need planning, and a corresponding hotline discovery method is proposed for traffic hotspot identification and hotline selection. To improve the scalability and efficiency of the proposed method in "Big Data" environment, the SAP HANA cloud is applied to implement the proposed method under two application scenarios. Finally, the experimental results demonstrate that the proposed method is both effective and efficient. Software—Practice and Experience. Copyright © 2016 John Wiley & Sons, Ltd.