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Characterizing the role of vehicular cloud computing in road traffic management

Authors :
Iftikhar Ahmad
Rafidah Md Noor
Ihsan Ali
Muhammad Imran
Athanasios Vasilakos
Source :
International Journal of Distributed Sensor Networks, Vol 13 (2017)
Publication Year :
2017
Publisher :
Hindawi - SAGE Publishing, 2017.

Abstract

Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles.

Details

Language :
English
ISSN :
15501477
Volume :
13
Database :
Directory of Open Access Journals
Journal :
International Journal of Distributed Sensor Networks
Publication Type :
Academic Journal
Accession number :
edsdoj.17c73fbe8d4f4fd98ac8747266c50106
Document Type :
article
Full Text :
https://doi.org/10.1177/1550147717708728