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Infrared Sensor based Self-Adaptive Traffic Signal System using Arduino Board

An infrared sensor based prototype of self-adaptive traffic signal control system has been developed in this paper. An autonomous traffic signal system can be an effective measure to alleviate congestion of urban traffic. The system adjusts the traffic signal parameters according to the intensity of...

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Bibliographic Details
Main Authors: Patel, Dhruv, Rohilla, Yogesh
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
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Summary:An infrared sensor based prototype of self-adaptive traffic signal control system has been developed in this paper. An autonomous traffic signal system can be an effective measure to alleviate congestion of urban traffic. The system adjusts the traffic signal parameters according to the intensity of vehicles in respective lanes and improves the efficiency of traffic operation on urban road networks. The self-adaptive traffic signal system is a closed loop control system. It measures the intensity of vehicles in each lane and gives a priority green signal to the lane, which has the highest intensity of vehicles and the red signal to every other lane. However, the priority depends on the type of road network and type of intersections. This infrared sensor based self-adaptive system measures the density of vehicles using infrared sensors at each of the four roads at the intersection. It sends data to Arduino Mega microcontroller board which accordingly gives priority to the most concentrated lane. A detailed description of each of the components with its pin diagram and technical details has been provided. The functioning of the system has been shown with the help of system architecture, a block diagram, a flow chart, and a closed loop control system diagram. The system has been simulated on Proteus 8 simulation software. A step by step process of hardware connections has been given so that anyone can make this prototype. The results of the prototype are exciting in controlling the traffic.
ISSN:2472-7555
DOI:10.1109/CICN49253.2020.9242560