The rapid advancement of huge technology of Big Data, its applications have grown increasingly diverse. The best gratitude for resolving traffic congestion in big cities is the appliance of Big data technologies in the intelligent system of transportation . The most common reasons of traffic congestion in large cities are examined in depth in this paper. Large scale data and associated traffic data supported by GPS are composedusing modern communication technologies and internet of things. To build a traffic prediction and vehicle prediction model the data analysis method is used. The forecasting model is used to estimate traffic stream in each and every direction of traffic intersections at a specific location and time. The likelihood of traffic flow and congestion at a specific location at a specific time, as well as pedestrian travel trajectory and travel habits predicted. Consider the effect of non-motorizedautomobiles and pedestrians on traffic congestion at the same time. To untangle traffic jam problems, use real-time traffic information monitoring and forecasting results. A helpful reference is provided for decisionmaking in metropolitan trafficjam and traffic flow solutions when combined with optimization and control strategy for traffic collaborative management.

Big data technology, Traffic systems, Machine Learning, Intelligent Transportation system