• Dr.K.Madhusudhan
• Yadavalli JayaKrishna
• Benguluri Mahendra
• Palamboku Jaya Sankar
• Golla Likitha

In developing countries like India, the population is significantly growing. As the population grows, the number of vehicles on the roads are also exponentially increasing, which results in increase in road accidents and traffic congestion. Specifically, when an emergency vehicle such as Ambulance or Fire engine gets stuck in traffic jam, saving the human life becomes difficult. Under such circumstances, a promising system which can clear the traffic congestions especially in peak hours and thereby providing a safe path for emergency vehicles is very much essential. Therefore, the concept of edge detection could be used, which is concerned with the identifying and localizing the image specific- discontinuances. The contrast or intensity related alterations often gives rise to those discontinuances that are useful in acquiring the insightful info pertaining to the road traffic conditions. In this work, by being able to incorporate the edge info that is hidden in the considered road traffic images, the traffic flows could be predicted better by detecting the mobility case shadows. By this way, the intrinsic edges of the object could be preserved for better traffic forecasting. By inculcating these image processing-based concepts in our proposed camera-based system, we will be able to manage and regulate the traffic signals at junctions when the emergency vehicle arrives, by allowing the vehicular easy passage to come out of the traffic congestions. The proposed system is modelled by means of an experimental setup using Arduino, Python, and LEDs which regulates a real time traffic scenario.

In developing countries like India, the population is significantly growing. As the population grows, the number of vehicles on the roads are also exponentially increasing, which results in increase in road accidents and traffic congestion. Specifically, when an emergency vehicle such as Ambulance or Fire engine gets stuck in traffic jam, saving the human life becomes difficult. Under such circumstances, a promising system which can clear the traffic congestions especially in peak hours and thereby providing a safe path for emergency vehicles is very much essential. Therefore, the concept of edge detection could be used, which is concerned with the identifying and localizing the image specific- discontinuances. The contrast or intensity related alterations often gives rise to those discontinuances that are useful in acquiring the insightful info pertaining to the road traffic conditions. In this work, by being able to incorporate the edge info that is hidden in the considered road traffic images, the traffic flows could be predicted better by detecting the mobility case shadows. By this way, the intrinsic edges of the object could be preserved for better traffic forecasting. By inculcating these image processing-based concepts in our proposed camera-based system, we will be able to manage and regulate the traffic signals at junctions when the emergency vehicle arrives, by allowing the vehicular easy passage to come out of the traffic congestions. The proposed system is modelled by means of an experimental setup using Arduino, Python, and LEDs which regulates a real time traffic scenario.

"TRAFFIC PREDICTION FOR INTELLIGENT TRANSPORTATION USING IMAGE PROCESSING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.f528-f532, March-2023, Available :http://www.jetir.org/papers/JETIR2303568.pdf

"TRAFFIC PREDICTION FOR INTELLIGENT TRANSPORTATION USING IMAGE PROCESSING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppf528-f532, March-2023, Available at : http://www.jetir.org/papers/JETIR2303568.pdf