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

Abstract

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