Short-Term Traffic Flow Prediction: Techniques and Methods

Abstract

With the development of the economy, the expansion of the city scale, the increase in the population of urban residents and the increase in the per capita car ownership, the traffic congestion problem has an increasing impact on urban operation. Especially during the peak period of commuting traffic and holidays in large cities, most cities are facing the serious problem of road congestion. In order to facilitate the travel of residents and reduce air pollution, it is very important to keep the main road of the city smooth and rapid passage of vehicles. Therefore, cities should vigorously develop short-time traffic flow prediction, and accurate prediction of short-time traffic flow is the key to realizing intelligent urban traffic operation and efficient traffic flow management improvement. This paper will talk about the time series prediction model of short-time traffic flow prediction methods and advantages and disadvantages to provide auxiliary support for solving the traffic congestion problem, provide efficient travel path decision-making guidance for urban residents, facilitate the saving of urban people's travel costs, and also provide effective police deployment decision-making information for the traffic management department.