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metadata.conference.dc.title: Enhancement on The Traffic Light Controller Based on FIS
metadata.conference.dc.contributor.*: D R Jaya Bhanu Rao
Ahmad Zakaria,
metadata.conference.dc.subject: Fuzzy Inference System
Traffic Management System
Fuzzy Rules 1-Oct-2016
metadata.conference.dc.description.abstract: The number of vehicles on the road have been significantly increasing every year throughout the world. This phenomenon has lead to a severe traffic congestion especially in many highly populated cities. In order to ease this congestion, an effective and robust traffic control system is necessary. The current method of controlling the traffic light is based on the ‘time-of the-day’ approach. With this technique, the switching of traffic light takes place at a constant cycle time everyday. A predetermined light control sequence in a specified duration has been implemented for peak hours and off- peak hours daily. This approach does not provide an efficient solution for a smooth control of the traffic flow. In the current practice, a traffic police officer will be placed on duty at designated junctions to control the traffic congestion. An improved traffic light control system based on fuzzy inference system(FIS) can be implemented to ensure a smooth traffic flow without long queues and delays. The main objective of this design of control system is to avoid long delays of traffic especially during peak hours and also to avoid any police personnel at the scene. The concept of fuzzy rules that have been incorporated is similar to the way a traffic police controls the traffic congestion. In this case, the duration the green light is extended or stopped depending on the number of vehiches approaching the junction and the length of the queue of the vehicles during the stop mode at the red light. A miniature working model for an isolated 3 –lane intersection junction with traffic lights has been constructed to demonstrate the fuzzy traffic light control system. The fuzzy controller has been designed and simulated in MATLAB with fuzzy logic toolbox. The fuzzy controller has been written in C code and loaded in Arduino Due microcontroller board to control the traffic lights. Data related to traffic parameters is collected in Arduino IDE environment. The final output in terms of time delay of the existing controller is then compared with output from the fuzzy controller in order to monitor the significant effectiveness of the improved controller.
metadata.conference.dc.identifier.uri: Advanced Processes and Systems in Manufacturing An International Conference
metadata.conference.dc.conference.year: 2016
Appears in Collections:Conference Papers

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