Intelligent traffic signal controller based on type-2 fuzzy logic and NSGAII

Abstract

Intelligent traffic signal control (TSC) system is important for the alleviation of traffic congestion. Usually, most of the researches about TSC focused on single intersection based on type-1 fuzzy set. Compared with type-1 fuzzy logic controller (FLC), type-2 FLC can deal with more uncertainties in the road traffic control system. Therefore, a type-2 FLC optimized by NSGAII (T2-NSGAII) is designed for TSC in a complex road network, in which the intersection's traffic signal time is dynamically adjusted by its own and adjacent intersections' traffic volumes to reduce global delay time and traffic congestion. In T2-NSGAII, the expert rule set and the parameters of the fuzzy membership functions are simultaneously optimized by NSGAII to achieve less time delay and traffic congestion. In the simulations of a six-intersection traffic network with different vehicular arrival rates, it is demonstrated that T2-NSGAII has better performance compared with vehicle actuated controller based on fixed-time control (FTC), type-1 FLC, type-2 FLC and isolatedly optimized Type-2 FLC and the total delay time could be reduced by 76.3%, 65.1%, 58.3% and 35.4% respectively.