Abstract
Traffic congestion has become a significant problem due to increasing vehicle usage. The main challenge is reducing traffic congestion and ensuring a smooth and safe traffic flow. Lately, image processing technology has been studied to improve traffic issues and make traffic light controllers more intelligent. It removes limitations in earlier standard traffic control systems. This paper proposes a traffic control system using Raspberry Pi and image processing techniques. The camera with a top viewing angle at the intersection monitors the four intersections in real-time. The captured images are processed using a series of image processing techniques. This method is performed on the recorded image to realize the identification and counting of cars. The Raspberry Pi calculates flexible green light duration based on the measured traffic density on the road. Most cars at intersections are given priority instead of cars with a small number. For the same amount, the system will prioritize vehicles on horizontal lane A first, along horizontal lane B, then along with vertical lane A, and finally along vertical lane B. The model was tested, and the model’s outcome was as expected.
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Zulkifli, A.R., Ali, K., Abd Rahman, Z. (2022). Raspberry Pi Based Intelligent Traffic Signal Control at Intersections. In: Wahab, N.A., Mohamed, Z. (eds) Control, Instrumentation and Mechatronics: Theory and Practice. Lecture Notes in Electrical Engineering, vol 921. Springer, Singapore. https://doi.org/10.1007/978-981-19-3923-5_34
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DOI: https://doi.org/10.1007/978-981-19-3923-5_34
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