[hpc-announce] Call for Papers -- SCPE -- Special Issue: Cloud Computing for Intelligent Traffic Management and Control

[Marcin Paprzycki]

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: zll.haut at gmail.com

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: eivanjko at fpz.unizg.hr

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: SSPulugurtha at uncc.edu

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.