MACHINE LEARNING

Detailed explanation-1: -Many researchers have used the clustering algorithm in short-term traffic flow predictions for a long time. For instance, the authors in [124] designed a model to support the Intelligent vehicle–highway systems, where the dynamic clustering algorithm was introduced.

Detailed explanation-2: -There are usually five parameters to evaluate, including traffic volume, traffic density, occupancy, traffic congestion index, and travel time while monitoring and predicting traffic congestions. Depending on the nature of the collected data, a variety of AI approaches are applied to evaluate the congestion parameters.

Detailed explanation-3: -To overcome the problem of traffic congestion, the traffic prediction using machine learning which contains regression model and libraries like pandas, os, numpy, matplotlib. pyplot are used to predict the traffic. This has to be implemented so that the traffic congestion is controlled and can be accessed easily.