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)

  1. Intelligent traffic signal control system based on cloud computing
  2. Cloud computing intelligent traffic scheduling platform
  3. Technologies of vehicle routing optimization based on cloud computing intelligent transportation
  4. Optimal route guidance service of intelligent transportation based on cloud computing
  5. Logistics monitoring and tracking system based on traffic cloud computing
  6. Traffic detection and prediction: navigation-based autonomous traffic avoidance
  7. Taxonomy of edge and cloud computing for connected vehicles
  8. 11.V2V VANET cloud and edge cloud for intelligent transportation and traffic management
  9. Application security and information privacy of intelligent transportation based on cloud computing
  10. Intelligent cloud-based integration of datasets (traffic, incidents, weather, construction activities, events, etc.) from disparate sourceData processing and parallelization of intelligent transportation systems based on cloud computiIntelligent zoned transportation system based on artificial intelligence and cloud computing and its methoIntelligent traffic management system based on cloud computing
  11. Application security and information privacy of intelligent transportation based on cloud computing
  12. 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.

Guest Editors

Zhenling Liu, Henan University of Technology, email: zll.haut@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@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@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.