IET ITS SI 2017 : IET Intelligent Transport Systems, Special Issue on Big Traffic Data Analysis and Mining
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IET ITS SI 2017 : IET Intelligent Transport Systems, Special Issue on Big Traffic Data Analysis and Mining
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| Dates | Invalid date (iCal) - 2017/08/21 |
| Homepage: | http://digital-library.theiet.org/files/IET_ITS_CFP_BTD.pdf |
| Location | |
| Location: | N/A, undefined |
| Important dates | |
| Submissions: | 2017/10/01T12:00:00 |
| Table of Contents | |
Call for Papers
IET Intelligent Transport Systems SPECIAL ISSUE ON: Big Traffic Data Analysis and Mining
Editors-in-Chief: Frank Lai, University of Leeds, UK and Margaret Bell, Newcastle University, UK
IET Intelligent Transport Systems seeks original manuscripts for a Special Issue on Big Traffic Data Analysis and Mining. In recent years, with the pervasive applications of intelligent transportation equipment such as GPS devices, traffic cameras, smart cards, and road deceleration devices, multisource traffic data are more easily collected than before. Analysing and mining the regularities hidden in traffic big data has been a hot research field associated with transportation management, urban planning, epidemic control, mobile platform application, and so on. This Special Issue will comprise state-of-the-art research in enabling Intelligent Transport Systems (ITS) with emphasis on big traffic data analysis and mining, including a broad range of enabling technologies in developing and optimizing the architecture, design, and operation of ITS.
Topics of interest include but are not limited to:
- Transportation optimization using big traffic data - Traffic control and management based on big traffic data - Transportation visualization based on big traffic data - Community activity prediction based on big traffic data analysis - Network science for big traffic data - Public transportation priority based on big traffic data - Data governance methods for big traffic data - Data privacy for big traffic data - Human behavior based on big traffic data - Human mobility prediction and visualization leveraging big traffic data - Big traffic data analysis for urban computing and decision-making - Modeling and data mining for big traffic data
All papers must be submitted through the journal's Manuscript Central system: http://mc.manuscriptcentral.com/iet-its
Submission Deadline: 1 October 2017 Publication Date: September 2018
Guest Editors: Feng Xia, Dalian University of Technology, China (Contact: f.xia@ieee.org) Jianxin Li, University of Western Australia, Australia Chakchai So-In, Khon Kaen University, Thailand Joel J. P. C. Rodrigues, National Institute of Telecommunications (Inatel), Brazil