Dynamic Traffic Light Control
S. Sasi Priya1, S. Rajarajeshwari2, K. Sowmiya3, P. Vinesha4, A. Athithya Janani5

1Dr. S. Sasi priya*, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
2Rajarajeshwari S., Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
3Indumathi G., Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
4Vinesha P., Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
5Athithya Janani A., Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore, India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on March 30, 2020. | PP: 3328-3331 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8609038620/2020©BEIESP | DOI: 10.35940/ijrte.F8609.038620

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).
Keywords: ITS, Traditional Traffic Management, Fleet Management, Adaptive Traffic Light Control, SUMO Simulator, Convolutional Neural Network
Scope of the Article: Digital Rights Management.