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Traffic Signal Timing Control Based on Vehicle Detection

Journal: International Journal of Science and Research (IJSR) (Vol.9, No. 4)

Publication Date:

Authors : ; ; ; ; ;

Page : 545-548

Keywords : Mathematical morphology; reinforcement learning; traffic congestion; simulation of urban mobility; monocular camera;

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Congestion of traffic is a major concern in many countries across the world. This problem has become a nightmare for the commuters in all cities across the world. This congestion on urban road networks has become increasingly problematic. In India, at every traffic signal, vehicles are stopped for a fixed period of time, which leads to traffic jam. Sometimes higher traffic density at one side of the road demands longer green signal time as compared to standard allotted time. This project focuses on object detection of images of vehicles on the road. The object detection in the traffic signal is processed and then its threshold is calculated. Based on this count, number of vehicles on the road is estimated. After calculating the number of vehicles on each side of the road, we will come to know on which side the density is high. According to density calculated, green signal time is estimated. The project also focuses on other concerns like applying strict traffic rules that ensures that citizens won’t break traffic laws. Rules like monitoring traffic, analyzing vehicles that drive on wrong side and many more are integrated in this project. It is the need of hour to monitor vehicles that break traffic rules as it leads to severe problems like congestion, accidents and may cost lives.

Last modified: 2021-06-28 17:03:45