Author(s): A.R. ZADE | D. R. DANDEKAR
Journal: International Journal of Computer Applications
ISSN 0975-8887
Volume: ncipet;
Issue: 2;
Date: 2012;
Original page
Keywords: Fuzzy | Inference System | Intelligent | Delays at Intersection | Simulink | Density | Flow rate
ABSTRACT
This paper presents a Simulation of Fuzzy Traffic Controller design for controlling Green Light time for effective traffic flow. Intelligent Traffic controllers are required these days to adjust to a situation of ever increasing traffic. Artificial Intelligence technique such as neuro-fuzzy systems, fixed time embedded controllers, etc. are available to handle the traffic related problems. But Adaptive traffic signal controller based on Fuzzy Inference System used in this project provides smart solutions for efficient traffic control. This system reflects two fundamental aspects of traffic responsive signal control- the observation of on-going traffic situation around the intersection, and the control of the traffic signals in a manner appropriate to the observed situation. In traffic signal control system, detection of traffic variables at intersection is very important and is the basic input data to determine signal timing. The controller is developed based on traffic density and traffic flow rate. This FIS module is developed in SIMULINK environment of MATLB tool which has achieved the satisfactory results for traffic signal control. The "Adaptive Traffic Signal Controller based on Fuzzy Inference system" is capable of taking decision to reduce delays at intersection.
Journal: International Journal of Computer Applications
ISSN 0975-8887
Volume: ncipet;
Issue: 2;
Date: 2012;
Original page
Keywords: Fuzzy | Inference System | Intelligent | Delays at Intersection | Simulink | Density | Flow rate
ABSTRACT
This paper presents a Simulation of Fuzzy Traffic Controller design for controlling Green Light time for effective traffic flow. Intelligent Traffic controllers are required these days to adjust to a situation of ever increasing traffic. Artificial Intelligence technique such as neuro-fuzzy systems, fixed time embedded controllers, etc. are available to handle the traffic related problems. But Adaptive traffic signal controller based on Fuzzy Inference System used in this project provides smart solutions for efficient traffic control. This system reflects two fundamental aspects of traffic responsive signal control- the observation of on-going traffic situation around the intersection, and the control of the traffic signals in a manner appropriate to the observed situation. In traffic signal control system, detection of traffic variables at intersection is very important and is the basic input data to determine signal timing. The controller is developed based on traffic density and traffic flow rate. This FIS module is developed in SIMULINK environment of MATLB tool which has achieved the satisfactory results for traffic signal control. The "Adaptive Traffic Signal Controller based on Fuzzy Inference system" is capable of taking decision to reduce delays at intersection.
