A Road Accident Prediction Model Using Data Mining Techniques

A Road Accident Prediction Model Using Data Mining Techniques

Prof. M. N. Jadhav, Pradeep Uttam Barve, Rushikesh Kishor Gaikwad, Yashwant Balasaheb Velamkar, Aishwarya Santosh Avhad

Computer Technology
K. K. WAGH POLYTECHNIC, Nashik

Abstract - Implantation of study on road accidents and the development of a prediction model using data mining techniques is indeed very important. The use of the Apriori algorithm and Support Vector Machines (SVMs) in developing an accident prediction model is a well-established approach123.The Apriori algorithm is used to explore the causal relationship between multiple factors, such as the condition of a road and environmental factors, to understand the mechanism of accidents4. SVMs, on the other hand, are powerful tools for classification and regression problems and can be used to analyze the severity of crashes. As for the Bangaloreroad accident datasets for the years 2014 to 2017, there are indeed datasets available on the internet that can be used for such studies567. These datasets, along with the insights from your study, can indeed be beneficial for various stakeholders, including government public work departments, contractors, and automobile industries, in better designing roads and vehicles based on the estimates obtained. It’s worth noting that road safety is a complex issue that involves various factors. While data analysis and prediction models can provide valuable insights, it’s also crucial to consider other aspects such as enforcement of traffic rules, driver education, and infrastructure development to effectively reduce road accidents.

Key Words:  Accident prediction, Data mining, Apriori algorithm, Rule mining, Classification