Smart City Gnosys

Smart city article details

Title	Ai-Based Dynamic Traffic Signal Control
ID_Doc	6989
Authors	Kalai Selvi T.; Ajaykannan R.; Boomika M.; Jeevitha C.; Dinesh R.
Year	2025
Published	Proceedings of 5th International Conference on Pervasive Computing and Social Networking, ICPCSN 2025
DOI	http://dx.doi.org/10.1109/ICPCSN65854.2025.11035294
Abstract	The AI-Based dynamic traffic signal control system aimed at improving traffic efficiency at four-way intersections. Traditional traffic signals operate on fixed time intervals, which often results in unnecessary delays and traffic congestion, especially during peak hours or in emergency situations. To address this, the proposed system incorporates real-time object detection using YOLOv5, a highly accurate and efficient deep learning model. The model processes video feeds from each road connected to the intersection, identifying the presence and type of vehicles approaching the signal. Special emphasis is placed on the detection of emergency vehicles such as ambulances, fire trucks, and police cars. This system continuously monitors traffic conditions and adjusts signal timings dynamically based on vehicle density and emergency vehicle presence, rather than relying on static schedules.A key feature of the system is its ability to prioritize emergency vehicles, ensuring they receive a green signal upon detection to facilitate quicker and safer passage through intersections. This is crucial for minimizing response times during critical situations, potentially saving lives. The architecture of the system includes integration between a trained YOLOv5 model enabling smooth and coordinated decision-making. By combining computer vision with intelligent control mechanisms, the system not only enhances overall traffic management but also supports the broader goal of smart city infrastructure. Simulation results and practical implementation scenarios demonstrate significant improvements in traffic flow and emergency response efficiency, validating the system's effectiveness and real-world applicability. © 2025 IEEE.
Author Keywords	AI-based system; Emergency vehicle prioritization; Object detection; Smart traffic management; Traffic signal control; YOLOv5

Similar Articles

Id	Similarity	Authors	Title	Published
51589	0.91	Talaat F.M.; El-Balka R.M.; Sweidan S.; Gamel S.A.; Al-Zoghby A.M.	Smart Traffic Management System Using Yolov11 For Real-Time Vehicle Detection And Dynamic Flow Optimization In Smart Cities	Neural Computing and Applications (2025)
4541	0.898	Ashkanani M.; AlAjmi A.; Alhayyan A.; Esmael Z.; AlBedaiwi M.; Nadeem M.	A Self-Adaptive Traffic Signal System Integrating Real-Time Vehicle Detection And License Plate Recognition For Enhanced Traffic Management	Inventions, 10, 1 (2025)
6366	0.893	Papanashi S.; Chadaga M.; Kshithi R.; Huddar S.S.; Sreelakshmi K.; Ramakanth Kumar P.	Adaptive Traffic Signal Timing: Leveraging Yolov10 And Computer Vision For Real-Time Optimization	8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024 (2024)
50560	0.89	Baiat Z.E.; Baydere S.	Smart City Traffic Monitoring:Yolov7 Transfer Learning Approach For Real-Time Vehicle Detection	2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023 (2023)
62130	0.89	Vijay Ganesh P.; Sam Joshua V.; Saro Murugan L.; Mahalakshmi S.	Yolov9 Driven Internet Of Things Enabled Sustainable Solution For Intelligent Traffic Light Management System For Emergency Vehicles In Large Scale Urban Traffic	2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025 - Proceedings (2025)
35950	0.889	Khan H.; Kushwah K.K.; Maurya M.R.; Singh S.; Jha P.; Mahobia S.K.; Soni S.; Sahu S.; Sadasivuni K.K.	Machine Learning Driven Intelligent And Self Adaptive System For Traffic Management In Smart Cities	Computing, 104, 5 (2022)
17876	0.888	Rajagopal M.; Sivasakthivel R.	Deep Learning For Intelligent Transportation: A Method To Detect Traffic Violation	AIP Conference Proceedings, 2763, 1 (2023)
62132	0.888	Gowri B.S.; Harini Harisitha S.; Abishek Kanna M.; Amirthavarshini N.S.	You Only Look Once Version 8 (Yolov8)-Driven Emergency Vehicle Detection And Graph Neural Networks (Gnns) Based Traffic Signal Prioritization	Proceedings of 5th International Conference on Trends in Material Science and Inventive Materials, ICTMIM 2025 (2025)
6715	0.887	Priya K.; Priyadharshini K.; Krishnan R.S.; Raj J.R.F.; Settu I.J.; Srinivasan A.	Advancing Urban Traffic Control With Iot And Deep Learning: A Yolov8 And Lstm-Based Adaptive Signal System	Proceedings of the International Conference on Intelligent Computing and Control Systems, ICICCS 2025 (2025)
40922	0.886	Duc Q.-A.N.; Kim T.D.; Nguyen Q.-C.; Thi T.H.N.; Vu Q.; Xuan M.-D.D.; Nguyen V.-N.	Optimizing Traffic Light Control Using Yolov8 For Real-Time Vehicle Detection And Traffic Density	Proceedings of the 2024 9th International Conference on Integrated Circuits, Design, and Verification, ICDV 2024 (2024)