FPGA IMPLEMENTATION OF INTELLIGENT TRAFFIC SIGNAL CONTROLLER BASED ON NEURO FUZZY SYSTEM (International Journal of Engineering and Computer Science, 2014)
The aim of this paper is to design, simulate, and synthesis a simple, suitable and reliable VLSI fuzzy processor for controlling the traffic lights. Fast, rapid, and vast transportation systems are nerves of economic development for any nation. This paper studies the deviation in traffic flow data and data bottleneck production problem, and provides a solution based on conjunction of mathematical statistics and time series analysis. The monitoring and control of city traffic is one of the key issues especially in metropolitan areas due to ever increasing number of vehicles and pedestrians. Present traffic controllers are based on microcontroller and microprocessor. These traffic light controllers have limitations because it uses the predefined hardware, which functioning according to program that does not have the flexibility of modification on real time basis. 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 paper starts with an overview of FPGA in order to get an idea about FPGA architecture, and followed by an explanation on the hardware implementation with both type analogue and digital implementation, a comparison between fuzzy and conventional controller also provided in this paper. The “Intelligent Traffic Signal Controller using FPGA controller based on Neuro-Fuzzy system” is capable of taking decision to reduce delays at intersection. To develop the system, algorithm need to be developed using VHDL. The designing part of this controller into VHDL program eliminates the shortcomings of the other custom facilities and conventional controller design available today.