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A fuzzy arithmetic-based analytical reliability assessment framework (FAARAF): case study, cognitive radio vehicular networks with drivers


Reliability is one of the main objectives of many systems, which may be part of man-machine systems, consisting of human operators and machines working under the specified conditions. Vehicular networks are systems in which safety information must be delivered reliably and quickly to ensure the driver’s correct and timely reaction. Hence, in this paper, we propose a general framework based on fuzzy arithmetic to perform a reliability assessment of different systems with various kinds of components. Then we apply the framework to a cognitive radio vehicular ad-hoc network (CR-VANET) with drivers (CRVD system). The reliability of a CRVD system depends on different environmental, vehicular, and human-related factors that change over time. The interactions between these factors are so convoluted and subjective. Hence, reliability estimation of the system with a crisp value is difficult. Moreover, there is a lack of consideration given to driver’s reaction in the system’s reliability estimations even though it is one of the most critical safety issues in intelligent transportation systems (ITS). The reliability analysis in the present study is performed for vehicular communications with and without considering the drivers. The analytical results are supported by simulations using NS3 and compared with existing methods. The evaluation results indicate that reliability is assessed more precisely when considering the driver as one of the system’s components.

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Correspondence to Naser Movahhedinia.

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Bahramnejad, S., Movahhedinia, N. A fuzzy arithmetic-based analytical reliability assessment framework (FAARAF): case study, cognitive radio vehicular networks with drivers. Computing (2021).

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  • Reliability assessment
  • Drivers
  • Fuzzy logic
  • Intelligent transportation systems (ITS)

Mathematics Subject Classification

  • 03B52
  • 68M15