Dynamic Fuzzy Logic-Ant Colony System-Based Route Selection System

Route selection in metropolises based on specific desires is a major problem for city travelers as well as a challenging demand ofcar navigation systems. This paper introduces a multiparameter route selection system which employs fuzzy logic (FL) for localpheromone updating of an ant colony system (ACS) in detection of optimum multiparameter direction between two desiredpoints, origin and destination (O/D). The importance rates of parameters such as path length and tra fficareadjustablebytheuser. In this system, online traffic data are supplied directly by a tra ffic control center (TCC) and further minutes tra fficdataare predicted by employing artificial neural networks (ANNs). The proposed system is simulated on a region of London, UnitedKingdom, and the results are evaluated.