Accident Prediction Modeling for Indian Metro Cities

Abstract

Road accidents are one of the biggest concerns to the road safety of developing nations. In India, around 150,000 fatal accidents occur annually. Road accident prediction models help in accessing the factors responsible for and those that contribute more to accidents. Most of the prediction models focus on the parameters like road characteristics, traffic characteristics, driver characteristics, and road geometrics. In this study, we considered socio-economic and land-use parameters as input data for accident prediction modeling. The socio-economic and land-use variables data of 20 Indian metro cities were collected. The data were collected for a period of 5 years ranging from 2016 to 2020. A multiple linear regression model was developed between the total number of accidents that happened in the 20 metro cities and the socio-economic and land-use variables. ANN model was also developed to check its applicability to this study and the results obtained are satisfactory.