Behavioral Analysis and Risk Assessment of Two-Wheeler Drivers

With the growing popularity of two-wheelers in urban and rural areas, it is imperative to enhance road safety and reduce the alarming rate of accidents involving two-wheeler riders. This study combines behavioral analysis, data collection, and risk assessment to provide insights that can be leveraged for developing effective road safety strategies.The "Behavioral Analysis of Two-Wheeler Drivers" project aims understand the behavior of driving patterns of individuals operating two-wheeled vehicles, such as motorcycles and scooters.

Models Trained:

1. LSTM (Long Short Term Memory)
2. GRU (Gated Recurrent Unit)
3. AdaBoost
4. XGBoost
5. MLP Ensemble (Multi-Layer Perceptron Ensemble)

Video Drive Link :- https://drive.google.com/file/d/1lLuHEtYv_poL6W6aVZ_PLAIpmZx39Ucx/view?usp=drive_link