Abstract
In this survey, we analyze the proposals of vehicular communication systems in the context of road traffic management. Starting with the definition of communications between vehicles (V2V), vehicles-to-infrastructure (V2I) and vehicles-to-everything (V2X), we first focus on the requirements and current standards for the Intelligent Transport Systems (ITS), including the maximum communication delay, the communication range and the size of messages (in the case of V2I transmission). After that, we analyze the use cases in line with the implementation of intelligent traffic management and review the respective methods that support or directly manage traffic on roads. One of the primary objectives of this paper is to highlight the architectures of four classes of systems able to support vehicular traffic management and communication between vehicles and roadside infrastructure, namely: vehicular cloud computing (VCC), cloudlets, Mobile Edge Computing (MEC) and fog computing. In this context, we also present our classification of the methods for these four classes of architectures. In the end, we provide our opinion on problems and limitations concerning the deployment of mechanisms belonging to each considered architecture class.
Citations
-
1 1
CrossRef
-
0
Web of Science
-
1 5
Scopus
Authors (2)
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/ACCESS.2022.3168354
- License
- open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
IEEE Access
no. 10,
pages 42365 - 42385,
ISSN: 2169-3536 - Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Jurczenia K., Rak J.: A Survey of Vehicular Network Systems for Road Traffic Management// IEEE Access -Vol. 10,iss. 10 (2022), s.42365-42385
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/access.2022.3168354
- Verified by:
- Gdańsk University of Technology
seen 255 times
Recommended for you
Developing Methods for Building Intelligent Systems of Information Resources Processing Using an Ontological Approach
- V. Lytvyn,
- V. Vysotska,
- M. Bublyk
- + 3 authors