R-CNN Model for the Traffic Signal Prediction

The density of crowd is less and the congestion speed is high, the system assumes that there is light congestion in the traffic. In intermediary conditions, traffic is characterized as moderately congested. The subsequent process introduces the process of estimating crowd density and vehicular speed on the premise of crowd segmentation and tracking. The traffic sign prediction techniques have certain steps. The deep learning model is applied for the prediction. The R-CNN is the deep learning which is the transform learning for the prediction of traffic signal. This project implements the new approach in Python software and evaluates it taking into account several performance measures.