Traffic Accident Risk Prediction using Machine Learning

K. LIKHITHA; J. ANASUYA; P. LAKSHMI; B. MOHAMMAD SHAMSHUDDIN; P.SHOBHA RANI

Traffic Accident Risk Prediction using Machine Learning

Author(s)	Mr. K. LIKHITHA, J. ANASUYA, P. LAKSHMI, B. MOHAMMAD SHAMSHUDDIN, P.SHOBHA RANI
Country	India
Abstract	Around 1.32 lakh human beings died because of street accidents in 2020, that's the best within the final eleven years. Earlier it changed into 1.26 lakh in 2009. Multiple street injuries fell to 3.Sixty six lakh inside the closing 12 months, the lowest fee inside the closing years. "The tough mechanisms hidden in those traditional devices are frequently the relationships among the elements that pressure accidents, and via breaking them open, we are able to enable them to lessen the superiority of accidents." At the equal time, several techniques to enhance protection are generally used to are expecting uncommon dangers, save you accidents and, ultimately, increase the level of safety inside the streets of the metropolis. At gift, corporate mining generates many ambiguous rules, surveys designed to assess task opportunities for small resource fees, and many automatic proposals for stricter regulation. Research outcomes display that these techniques are powerful in unit paper. Corporate standards are consequently incorporated into the automated improvement of modeling to enable the efficient use of corporate standards mining to attach the smart environment. Road protection is one in every of the most important priorities of governments these days. Many safety devices are built into motors, but website tourist injuries are commonplace and unavoidable. Reducing the harm resulting from injuries and assessing the reasons is the most crucial aim. In this case, it's far useful to examine the frequency of injuries, in order that the ones facts may be used to broaden techniques to lessen accidents. We can hypothesize a relationship between the effect of environmental factors on traveler website accidents, avenue situations and random attendance. I actually have used tree pruning, random wooded area and logistic regression and structures matching techniques to increase a risk prediction model. The improvement of safety features and risk evaluation can gain from those category frameworks. Several factors are used to are expecting bystander chance, including weather conditions, vehicle conditions, pavement situations, and lighting fixtures. Three data documents are loaded in this email: Accidents, Accidents and Vehicles. In this way the severity of accidents can be assessed.
Keywords	Road Accident, Vehicle, Automation, Accident Prediction, Accident, Factors
Field	Engineering
Published In	Volume 17, Issue 2, April-June 2026
Published On	2026-04-04

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Traffic Accident Risk Prediction using Machine Learning

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