Identify Discriminatory Factors of Traffic Accidental Fatal Subtypes using Machine Learning Techniques

In today's world, traffic accidents are one of the main reasons of mortality and long-term injury. Bangladesh is no exception in this case. Several vehicle accidents each year have become an everyday occurrence in Bangladesh. Bangladesh's largest highway, the Dhaka-Banglabandha National Highway, has a significant number of accidents each year. In this work, we gathered accident data from the Dhaka-Banglabandha highway over an eight-year period and attempted to determine the subtypes present in this dataset. Then we tested with various classification algorithms to see which ones performed the best at classifying accident subtypes. To describe the discriminatory factors among the subtypes, we also used an interpretable model. This experiment gives essential information on traffic accidents and so helps in the development of policies to reduce road traffic collisions on Bangladesh's Dhaka-Banglabandha National Highway.

@article{Loskor2022,
  title     = {Identify Discriminatory Factors of Traffic Accidental Fatal Subtypes using Machine Learning Techniques},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {2},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {W. Z. Loskor and Sharif Ahamed},
  doi       = {10.14569/IJACSA.2022.0130230},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130230}
}