KNOWLEDGE BASED TRAFFIC SIGNAL CONTROL MODEL FOR SIGNALIZED INTERSECTION

Abstract

Intelligent transportation systems have received increasing attention in academy and industry. Being able to handle uncertainties and complexity, expert systems are applied in vast areas of real life including intelligent transportation systems. This paper presents a traffic signal control method based on expert knowledge for an isolated signalized intersection. The proposed method has the adaptive signal timing ability to adjust its signal timing in response to changing traffic conditions. Based on the traffic conditions, the system determines to extend or terminate the current green signal group. Using the information from its traffic detectors of isolated intersection, the proposed controller gives optimal signals to adapt the phase lengths to the traffic conditions. A comparative analysis between proposed control algorithm, fuzzy logic (FLC) and fixed-timed (pre-timed) controllers has been made in traffic flows control, with varying traffic volume levels, by using simulation software ‘Arena’. Simulation results show that the proposed traffic signal control method (EKC) has better performance over fuzzy logic and conventional pre-time controllers under light and heavy traffic conditions.