Abstract
Traffic signals are essential to ensure safe driving at road intersections and to maintain a constant flow of vehicles in a convenient manner. However, sometimes inefficient traffic control themselves restrict the constant flow creating commotions and delays. Therefore, in this work, we are introducing a generalized smart traffic regulation algorithm (G-STRA) which is going to consider the real-time traffic density using image processing at each lane, to reduce the wait time and improve the total throughput. The system will be smart enough to identify vehicles of importance (VoIs), to give them extra clearance from the regular commuting vehicles. The G-STRA is called “smart” as it will adapt itself with the phases of the day, days of importance (DoIs), the condition of road, and weather and the type of commotion to predict the type of flow it should maintain learning from its past experiences.
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Narnolia, V., Jana, U., Chattopadhyay, S., Roy, S. (2020). Generalized Smart Traffic Regulation Framework with Dynamic Adaptation and Prediction Logic Using Computer Vision. In: Mandal, J., Bhattacharya, D. (eds) Emerging Technology in Modelling and Graphics. Advances in Intelligent Systems and Computing, vol 937. Springer, Singapore. https://doi.org/10.1007/978-981-13-7403-6_24
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DOI: https://doi.org/10.1007/978-981-13-7403-6_24
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