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The authors present a fuzzy traffic controller (FTC) with adaptive strategies, using two different defuzzification and decision-making criteria, for urban traffic control systems. The basic adaptive strategies employed here adjust the membership functions according to the traffic conditions to optimize the controller's performance. The methods are statistical-adaptive and fuzzy-adaptive, respectively. The FTC, which is composed of a fuzzy logic controller (FLC), a state machine, and an adaptive module, is described. A case study concerning the application of the proposed FTC at the intersection of two major avenues of the city of Sao Paulo is discussed. The results show that the FTC outperformed conventional control strategies and alternative fuzzy control schemes.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Favilla et al. (2002) studied this question.
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