Smart Traffic Signal Control System Using Vehicle Detection and Machine Learning | IJORET – Volume 11- Issue 2 | IJORETV11I2P6

Traffic congestion is a major problem in urban areas due to the rapid increase in vehicles. Traditional traffic signal systems use fixed time intervals, which lead to inefficient traffic flow and increased waiting time. This paper proposes a Smart Traffic Signal Control System that dynamically adjusts signal timing based on vehicle density. The system uses video input to detect vehicles and applies a machine learning-based approach to predict the green signal duration. A rule-based model is used to calculate optimal signal timing. The system improves traffic efficiency, reduces congestion, and minimizes waiting time. The implementation is carried out using Python, and results show better performance compared to conventional systems.

Smart Traffic Signal Control System provides an efficient solution for managing traffic based on real-time vehicle density. By dynamically adjusting signal timings instead of using fixed intervals, the system reduces waiting time and improves overall traffic flow. The integration of vehicle detection, a rule-based machine learning model, and signal control demonstrates a simple yet effective approach to intelligent traffic management. The system is cost-effective, scalable, and can be further enhanced for real-world smart city applications.

[1]Smith, J., “Smart Traffic Management System Using Machine Learning,” IEEE Transactions on Intelligent Transportation Systems, 2022. [2]Kumar, R., “Vehicle Detection Using Computer Vision Techniques,” International Journal of Engineering Research and Technology (IJERT), 2021. [3]Lee, S., “Intelligent Traffic Control Systems for Smart Cities,” Springer Publications, SSS2020. [4]Brown, T., “Machine Learning Approaches for Traffic Signal Optimization,” Elsevier, 2019. [5]Zhao, Y., “Real-Time Traffic Flow Prediction Using Deep Learning,” IEEE Access, 2021. [6]Chen, L., “Vehicle Detection and Tracking Using YOLO,” International Journal of Computer Vision, 2022. [7]Gupta, A., “Adaptive Traffic Signal Control System,” International Journal of Advanced Research in Computer Science, 2020. Patel, M., “IoT-Based Smart Traffic Management System,” Journal of Engineering Science and Technology, 2021. [Citation Format]

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