Vehicular Ad hoc Network (VANET) is a unique subset of mobile ad hoc networks (MANET), with the difference that nodes are vehicles provided with their own communication technology and interact to form spontaneous networks, with little or no infrastructure previously established. VANETs support the integration of different wireless technologies in order to mitigate adversities, add security and efficiency to traffic. In the data dissemination, a single hop is sufficient to guide the elements within reach of the radio signal, and intermediary nodes support the communication with the others in multihop routing. Supported by embedded devices, vehicles produce records, detect signals, exchange warnings and metrics. Assessments of this information allow the driver to make decisions or react beforehand in adverse situations, such as accidents or traffic congestions. From the observations in this context, this work deals with questions to elaborate intelligent adaptive strategies in data dissemination, since they consolidate themselves as ballast communication in VANET with adverse operating conditions. The proposed approach uses fuzzy systems to detect traffic congestion, with the purpose of aggregating autonomy and adapting the dissemination strategy to the identified traffic conditions. The convergence in the developments performed is reflected in the eFIRST strategy, a robust solution for the autonomous detection of the current traffic congestion condition that protects the adaptive dissemination of alerts and reduces the problem of the interruption in the traffic. The approach is supported only by communication between vehicles and in local neighborhood identification records, aggregated in a fuzzy strategy and in the adaptive adjustment of transmission signal power. In accordance with the driving trends and with the intelligent systems, this development contributes with assistance for ratify the fuzzy approach as an adaptive strategy to fluctuations in vehicular density in different scenarios and traffic regimes. Comparative evaluations of eFIRST support the conclusion that the strategy favors the optimal balance of losses, collisions and coverage, with a greater range of propagation and reduction of congestion.
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