Optimization of Transmission Signal Power through Observation of Congestion in VANets Using the Fuzzy Logic Approach: A Case Study in Highway and Urban Layout

Abstract

Vehicular ad hoc networks (VANETs) have unique features and rely on vehicle-to-vehicle (V2V) communication to mitigate adversities in traffic dynamics management and to support drivers providing safety alerts. Congestions, originating from an incident, frequently endanger traffic and, consequently, cause all kinds of losses. In this scenario, the paper herein proposes eFIRST, a robust solution to autonomous detection of the current congestion condition in order to disseminate safety alerts and to reduce problems with the interruption of traffic in a section of the highway. The approach is supported only by V2V communication and the local neighborhood identification records, which are brought together in a fuzzy strategy and in the adaptive adjustment of the transmission signal power. The estimate of local traffic conditions establishes the dynamic reach of transmission for the vehicle, supporting the connective maintenance. In these circumstances, the drivers receive an alert emitted soon enough for the proper response action. The results during simulations show how the elaborated solution leads to minimized delays, with low communication overload, besides relevantly mapping the congest levels and efficiently providing the event coverage to satisfactory propagation distances inside the area of interest for the dissemination. Promptly, the alert finds vehicles far from the traffic accident located at nearly 1/6 from the evaluated extension. In accordance with the intelligent protocols, this evaluation contributes providing grants for the ratification of fuzzy approximation as an adaptive strategy to fluctuations in vehicular density in different traffic basis.