View source for IET ITS SI 2017 : IET Intelligent Transport Systems, Special Issue on Big Traffic Data Analysis and Mining

{{Event 
|Field=computer science
|Submission deadline=2017/10/01T12:00:00
|Acronym=IET ITS SI 2017
|End date=2017/08/21
|Type =Conference
|Country=undefined
|City =N/A
|Homepage=http://digital-library.theiet.org/files/IET_ITS_CFP_BTD.pdf
|Start date=Invalid date
|Title=IET ITS SI  2017 : IET Intelligent Transport Systems, Special Issue on Big Traffic Data Analysis and Mining
}}
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