Fuzzy risk-based decision method for vehicular ad hoc networks

Shaikh, Riaz Ahmed ORCID: https://orcid.org/0000-0001-6666-0253 (2016) Fuzzy risk-based decision method for vehicular ad hoc networks. International Journal of Advanced Computer Science and Applications, 7 (9). pp. 54-62. ISSN 2158-107X

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Abstract

A vehicular ad hoc network (VANET) is an emerging technology that has the potential to improve road safety and traveler comfort. In VANETs, mobile vehicles communicate with each other for the purpose of sharing various kinds of information. This information is very useful for preventing road accidents and traffic jams. On Contrary, bogus and inaccurate information may cause undesirable things, such as automobile fatalities and traffic congestion. Therefore, it is highly beneficial to consider risk before vehicle takes any decision based on the received information from the surrounding vehicles. To overcome these issues, we propose a new risk-based decision method for vehicular ad hoc networks. It determines a risk-based the three key elements: 1) application type and sensitivity level, 2) vehicle context and 3) driver’s attitude. This paper also provides theoretical analysis and evaluation of the proposed method, and it also discusses the applications of the proposed model.

Item Type:	Article
Additional Information:	This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Uncontrolled Keywords:	sdg 9 - industry, innovation, and infrastructure ,/dk/atira/pure/sustainabledevelopmentgoals/industry_innovation_and_infrastructure
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory
Depositing User:	LivePure Connector
Date Deposited:	03 May 2023 15:30
Last Modified:	08 May 2023 00:07
URI:	https://ueaeprints.uea.ac.uk/id/eprint/91985
DOI:	10.14569/ijacsa.2016.070908

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