Call for Papers

Scalable Computing; Practice and Experience
www.scpe.org

(https://scholar.google.com/citations?hl=en&view_op=list_hcore&venue=DdKyR7ybz34J.2022)

A Special Issue on: Cloud Computing for Intelligent Traffic Management
and Control


Introduction

Cloud computing is known as a service delivery method for shared
resources, platforms, software, and data, in the interest of
end-users. With the continuous development of electronic information
technology (IT) and growth in the transportation engineering field,
cloud computing technology is widely used in intelligent traffic
management and control, and has become the inevitable trend.

Current transportation information service systems are facing
challenges associated with the integration and use of data from
related but diverse sources to manage the traffic and address people's
problems. Dealing with large amounts of transportation-related
information, data mining, traffic analysis, and dissemination promptly
are the key problems for future transportation information service
systems. Cloud computing technology, with its automated IT resource
scheduling and the advantages of the rapid deployment and excellent
expansivity, is an important technical means to solve this problem.

To alleviate urban traffic congestion, improve mobility, and ensure
traffic safety through intelligent traffic management and control,
this special issue contributes to the structural framework of
intelligence in transportation systems by combining cloud computing
models with intelligent traffic management and control. It aims to
explore the computing capability, system integration capability,
information integration capability, and personalized service
capability of cloud computing, which can make up for the difficulties
in sharing between subsystems of the current intelligent traffic
management and control systems, the delay in data analysis and
processing, and the latency in information transmission as well as
dissemination. It also accelerates the research on the promotion and
application of intelligent transportation-related cloud computing
systems, to enhance the level of traffic management and control, and
improve operational performance.


Recommended topics (but not limited to):

* Intelligent traffic signal light control system based on cloud computing
* Cloud computing intelligent traffic scheduling platform
* Technologies of vehicle routing optimization based on cloud
computing intelligent transportation
* Optimal route guidance service of intelligent transportation based
on cloud computing
* Logistics monitoring and tracking system based on traffic cloud computing
* Traffic detection and prediction: navigation-based autonomous
traffic avoidance
* Taxonomy of edge and cloud computing for connected vehicles
* 11.V2V VANET cloud and edge cloud for intelligent transportation and
traffic management
* Application security and information privacy of intelligent
transportation based on cloud computing
* Intelligent cloud-based integration of datasets (traffic, incidents,
weather, construction activities, events, etc.) from disparate sources
* Data processing and parallelization of intelligent transportation
systems based on cloud computing
* Intelligent zoned transportation system based on artificial
intelligence and cloud computing and its method
* Intelligent traffic management system based on cloud computing
* V2V VANET cloud and edge cloud for intelligent transportation and
traffic management
* Application security and information privacy of intelligent
transportation based on cloud computing
* Intelligent cloud-based integration of datasets (traffic, incidents,
weather, construction activities, events, etc.) from disparate sources


Important dates

Submission deadline:            30 November, 2022

Authors notification:           31 January, 2023

Final version submission:       28 February, 2023


Submission guidelines

Original and unpublished works on any of the topics aforementioned or
related are welcome. The SCPE journal has a rigorous peer-reviewing
process and papers will be reviewed by at least two referees. All
submitted papers must be formatted according to the journal's
instructions, which can be found here:
http://www.scpe.org/index.php/scpe/about/submissions#authorGuidelines


Guest Editors

Zhenling Liu, Henan University of Technology, email: [log in to unmask]

Zhenling Liu is an Associate Professor at the Marketing Research
Department, Henan University of Technology. His research interests
cover energy-economy-environment systems, energy economics, and
sustainable development. He has been the guest editor of special
issues for more than 10 journals and peer-reviewers of more than 30
times for different journals with 2 books published. Prof. Liu has
been selected as keynotes speakers 5 times at international
conferences. He is the Editor in Chief for the international Journal:
Adv. Indus. Eng. Manage, and the Associate Editor: Journal of Coastal
Research (IF=0.79), with an H-Index of 21 and 5 Highly Cited Papers by
Web of Science, Clarivate Analysis.


Edouard Ivanjko, University of Zagreb, email: [log in to unmask]

Edouard Ivanjko is an Associate Professor at the Department of
Intelligent Transportation Systems (ZITS), Faculty of Traffic and
Transport Sciences (UNIZG-FTTS), University of Zagreb (UNIZG) where he
teaches courses related to computer science, electrical engineering,
artificial intelligence, virtual reality, and traffic control. He is a
member of the Transport Optimization Group (TOG) at the Department of
Intelligent Transportation Systems (ZITS), Center of Excellence for
Computer Vision (CRV), and the Centre of Research Excellence for Data
Science and Advanced Cooperative Systems, Research unit Data Science.
Personal research interests include intelligent transportation
systems, modelling and simulation of road networks, application of
computer vision, and artificial intelligence in road traffic control.
In collaboration with research colleagues, he assists also in research
related to the development of algorithms for transport optimization,
estimation and prediction of traffic parameters, and navigation of
autonomous vehicles.


Srinivas S. Pulugurtha, The University of North Carolina at Charlotte,
email: [log in to unmask]

Srinivas S. Pulugurtha, P.E., F.ASCE is currently working as Professor
& Research Director of the Department of Civil & Environmental
Engineering at The University of North Carolina at Charlotte (UNC
Charlotte). He is also currently directing the Infrastructure, Design,
Environment, and Sustainability (IDEAS) Center on UNC Charlotte
campus. His research interests include transportation
planning/modeling and traffic simulation; intelligent transportation
systems (ITS); traffic safety; geographic information systems.

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