Deep learning: Spatial-Temporal road traffic data congestion using Agglomerative Clustering

In the long run of road traffic data especially in urbanization due to people migration because of employment and other factors still it is a challenging issue in daily life to recover the congestion. In our paper, the causes of road traffic data and its measures have been shown. The algorithm to alternate the route for people in case of traffic has been displayed in flowchart. The different types of traffic sign detection to alert the people in common on road traffic has been discussed with colors. The estimation of road traffic congestion is computed using necessary formulas has been shown. Various measures have been calculated show the higher accuracy of agglomerative clustering compared with other models. The experimental study has been shown in Real Time traffic data of Chenmai city from the year 2015 to 2021. In addition, drastic measures to control road traffic congestion has been discussed for present and future