A Multi-Agent system for road traffic decision making based on Hierarchical Interval Type-2 Fuzzy Knowledge Representation System

Abstract

Traffic congestion is a problem in most large cities world wide. It occurs when the capacity of road is surpassed, resulting in augmented vehicular queuing and slower average speeds. The traffic congestion can be caused or increased by various conditions like weather, road work, road traffic incidents. To deal with these problems, we propose a novel cooperative Multi-Agent system (MAS) for Road Traffic Decision Making in Vehicular Ad-Hoc network (VANET) based on a Hierarchical Interval Type-2 Fuzzy Knowledge Representation System (CMRHFS) used for travel route guidance. Our proposal aims to increase the road safety and the quality of the entire road network, especially in case of congestions, accidents and jams, considering traffic information in real-time as well as drivers travel time to attain their destinations. The obtained simulation results have proved our suggested system efficiency compared to Dijkstra's algorithm and Hierarchical Interval Type-2 Fuzzy Logic System (HIT2FLS) regarding two criteria: average travel time and path flow.