Smart Control of Traffic Light Using Artificial Intelligence

M. Sravani; S. Geetha Sri Priyanka; K.N.V.K Sairam; K. Krishna Murthy

doi:10.32628/CSEIT25111282

Authors

M. Sravani M. Tech, Computer Science and Engineering, PPDV, Andhra Pradesh, India Author
S. Geetha Sri Priyanka Assistant Professor, Computer Science and Engineering, PSCMR, Andhra Pradesh, India Author
K.N.V.K Sairam M. Tech, Computer Science and Engineering,, PPDV, Andhra Pradesh, India Author
K. Krishna Murthy Professor, Computer Science and Engineering, PPDV, Andhra Pradesh, India Author

DOI:

https://doi.org/10.32628/CSEIT25111282

Keywords:

Computer Vision, Traffic management, Traffic light system, Traffic congestion, Artificial intelligence, Smart surveillance

Abstract

Traffic light management is one of the intense technical hazards of the urban areas in almost every country around the world. This is due to speedy increase in number of vehicles in order to decrease the time and complexity. The project developed by us will enable the traffic light to switch from red to green based on traffic density. The easy way to control a traffic light by using timer for each section since, we proposed a system for controlling the traffic light by image processing. The system can notice vehicles through pictures and also the image sequence can then be analyzed victimization digital image process for vehicle detection, and in line with traffic conditions on the road stoplight will be controlled.

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References

Tom Tom World Traffic Index, 2019, [online] Available: https://www.tomtom.com/en_gb/trafficindex/ranking/.

Khushi, "Intelligent Traffic Signal Control System using Image Analysis," 2017 Global Symposium on Current Developments in Computer, Electrical, Electronics, and Communication (CTCEEC) Mysore, pp. 99- 103, 2017. DOI: https://doi.org/10.1109/CTCEEC.2017.8454966

Khekare, G.S.; Sakhare, A.V., "A smart city framework for intelligent traffic system using VANET," Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), 2013 International Multi-Conference on , vol., no., pp.302,305, 22-23 March 2013. DOI: https://doi.org/10.1109/iMac4s.2013.6526427

‘Traffic Signal Synchronization’. [Online]. Available:https://www.cityofirvine.org/signal-operations-maintenance/trafficsignal-synchronization.

Open Data Science, ‘Overview of the YOLO Object Detection Algorithm’, 2018. [Online].Available:https://medium.com/@ODSC/overview-of-the-yolo-object-detection-algorithm-7b52a745d3e0.