A Survey on Traffic Flow Prediction Methods

Abstract

In order to grow efficiency in Intelligent Transportation System (ITS), a number of dynamic route guidance scheme has been designed to assist driver in determining the optimal route for their journeys. To determine an optimal route, utilizing real-time traffic information is a key factor in improving traffic efficiency. Not only being able to utilize the real-time traffic information, but prediction of the traffic proves as one of the important aspects in improving traffic efficiency. In this paper, we will discuss various methods related to traffic flow prediction in ITS that will eventually lead to a proposed method. We will review some papers related to traffic flow prediction methods. Traffic flow prediction method is divided into two general types: Short-Term Prediction method and Long-Term Prediction method. Short-Term Prediction method relies on real-time information; however, this method can be redundant for a daily recurring traffic condition. On the other end, Long-Term Prediction relies on time series collective data from traffic condition routine, but this method is vulnerable to atypical traffic conditions like accident or road work. In the end, the author will propose a method to create a new sufficient method. This proposed method is a traffic prediction method that combines dynamic real-time information prediction (short-term prediction) and time series analysis prediction (long-term prediction).