A Case Study on Highway Flow Model Using 2-D Gaussian Mixture Modeling

Traffic flow prediction is very important for real time information of travelers and dynamic route guidance system. In the past, various methodologies have been developed for traffic flow prediction. However, most of existing methods for the formulation of traffic flow are complex. In this paper, using a 2-D histogram projection method, a temporal-spatial traffic flow data is first reduced to a 2-D scatter plot and a 2-D Gaussian Mixture Modeling (GMM) is then used to estimate the traffic flow. This study shows that the traffic flow data can be simply represented by a linear combination of multiple Gaussian functions which demonstrates a good visualization of the temporal-spatial traffic flow data.