A Fuzzy-Based System for Assessment of Recognition Error in VANETs Considering Inattentive Driving as New Parameter

This paper introduces an innovative system that uses Fuzzy Logic (FL) to detect recognition errors in Vehicular Ad Hoc Networks (VANETs). The system considers various input parameters to assess recognition errors in VANETs. In our previous work, we considered three parameters: Internal and External Distraction, Driver’s Inattention, and Inadequate Surveillance. In this paper, we consider Inattentive Driving as a new parameter. By employing FL, we model complex relationships and uncertainties in different situations. This approach transforms multifaceted input data into actionable insights regarding recognition error likelihood. We consider both driver-related and external factors, which affect the recognition accuracy. The simulation results show that the proposed system effectively captures different driver attention situations and environmental conditions. The proposed system can enhance VANET performance by enabling more adaptive and responsive vehicular communication in dynamic road environments.