Abstract: There has been a tremendous growth of vehicles in developing countries in the last decade. The growth of vehicles has led to increase in traffic volume and increased number of road trips. Further, this scenario has led to increase in road traffic accidents. The deaths and injuries due to road accidents are posing a major concern and challenge, globally, due to its socio-economic costs. The causative factors of accidents are the complex interaction between the various road-user and vehicle-environment related factors. However, prediction of future accidents and variables responsible for occurrence of accidents is of utmost importance to appreciate the quantum of problem and speed up the decision making. Moreover, the Indian two lane highways carry mixed traffic which has a lot of variability. This further affects the explanatory variables responsible for accidents. Accident prediction modelling enables traffic engineers to analyze why an accident happens and correlate mathematically the causal factors to accident occurrence. In this study, an attempt is made to explore the potential of Neural Networks for highly complex and nonlinear relationship of variables influencing accidents on the study stretch of NH-7. The results suggested that ANN approach is a very useful computational tool for analyzing and predicting traffic accidents.
Keywords: Traffic, Artificial Neural Network, Accident Modelling, Minitab, Two Lane Roads.
Title: ACCIDENT MODELLING ON NH-7 USING ARTIFICIAL NEURAL NETWORK
Author: Nirpinder Jain, Dr. Sanjiv Kumar Aggarwal
International Journal of Interdisciplinary Research and Innovations
ISSN 2348-1218 (print), ISSN 2348-1226 (online)
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