Risk-Based decision methods for vehicular networks

Shaikh, Riaz Ahmed and Thayananthan, Vijey (2019) Risk-Based decision methods for vehicular networks. Electronics (Switzerland), 8 (6). ISSN 2079-9292

Full text not available from this repository. (Request a copy)

Abstract

Vehicular networks play a key role in building intelligent transport systems for smart cities. For the purpose of achieving traffic efficiency, road safety, and traveler comfort, vehicles communicate and collaborate with each other as well as with the fixed infrastructure. In practice, not all vehicles are trustworthy. A faulty or malicious vehicle may forward or share inaccurate or bogus information, which may cause adverse things, such as, road accidents and traffic congestion. Therefore, it is very important to evaluate risk before a vehicle takes any decision. Various risk-based decision systems have already been proposed in the literature. The fuzzy risk-based decision model of vehicular networks is one of them. In this paper, we have proposed various extensions in the fuzzy risk-based decision model to achieve higher robustness, reliability, and completeness. We have presented the theoretical and simulation-based analysis and evaluation of the proposed scheme in a comprehensive manner. In addition, we have analytically cross verified the theoretical and simulation-based results. Qualitative comparison of the proposed scheme has also been presented in this work.

Item Type: Article
Additional Information: Funding Information: This article contains the results and findings of a research project that is funded by King Abdulaziz City for Science and Technology (KACST) Grant No. LGP-36-215. Funding Information: Funding: This article contains the results and findings of a research project that is funded by King Abdulaziz City for Science and Technology (KACST) Grant No. LGP-36-215. Publisher Copyright: © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
Uncontrolled Keywords: decision methods,risk methods,vehicular networks,control and systems engineering,signal processing,hardware and architecture,computer networks and communications,electrical and electronic engineering,sdg 9 - industry, innovation, and infrastructure,sdg 11 - sustainable cities and communities ,/dk/atira/pure/subjectarea/asjc/2200/2207
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 16 Aug 2022 15:31
Last Modified: 24 Sep 2022 07:03
URI: https://ueaeprints.uea.ac.uk/id/eprint/87323
DOI: 10.3390/electronics8060627

Actions (login required)

View Item View Item