Article Details

Development of Road Traffic Accident Prediction Model by Using Artificial Neural Network: A Case Study of Mumbai-Pune Expressway | Original Article

Neha Kasar*, R. R. Sorate, in Journal of Advances in Science and Technology | Science & Technology


People's lifestyles have improved as a result of the rapid development in urbanisation. However, these developments have placed a burden on roadways by expanding vehicle ownership, causing traffic problems to worsen at an alarming rate. The primary cause of road traffic accidents could be an increase in the rate of traffic volume. In rapidly developing metropolitan agglomerations, road traffic accidents are a big concern. There is a substantial body of research literature that sheds light on the scope of the problem and the remedies that are required. Road traffic accidents are the third leading cause of unnatural death among all deaths. Transportation engineers and academics have attempted to construct safe roads that adhere to suitable design standards, yet traffic accidents are inescapable. If an accident occurs, the reasons that caused it must be identified, and suitable corrective measures must be established and implemented as soon as possible. The goal of this study is to gain a better knowledge of the problem of road traffic accidents on the Mumbai Pune Expressway (MPEW) and the factors that may contribute to the high accident rates. Using Artificial Neural Networks, this research will construct an accident prediction model to anticipate the amount of accidents along the MPEW (ANN)