• MUDUNURU KALYAN VARMA

A high accident risk prediction model is built in this work to examine methods for Traffic Accident severity prediction and identify priority intersections for improvement. A traffic accident database was compiled and examined, and a junction accident risk prediction model based on it was developed. different methods were created to predict the possible high accident risk Using Gaussian Blur, Otsu’s thresholding, and Character segmentation algorithm. Image Processing was used to develop an accident risk prediction model. This model can also identify the key factors that affect the occurrence of high-risk intersections. The ability to predict the risk of traffic accidents is important in the prevention of the occurrence of accidents and to reduce the damages caused by accidents proactively. This paper introduces a new way of method for Traffic Accident severity prediction Using the same environmental characteristics as high-risk intersections for model inputs for estimating the level of danger that may occur in the future, which can be utilized to prevent future traffic accidents. The main issue of this paper is to make the probability of a road accident and warn the user based on the predicted risk. The risk is calculated based on challans that are registered with the vehicles.

image processing, risk prediction, traffic accident intersection, challans.

"METHOD FOR TRAFFIC ACCIDENT SEVERITY PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.b107-b112, October-2021, Available :http://www.jetir.org/papers/JETIR2110112.pdf

"METHOD FOR TRAFFIC ACCIDENT SEVERITY PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppb107-b112, October-2021, Available at : http://www.jetir.org/papers/JETIR2110112.pdf