Identifying the Stay Point Using GPS Trajectory of Taxis

Abstract

With the widespread use of personal mobile communications location-aware devices, a large amount of data of trajectory produced and can be used in information services. These huge amounts of data involves the pattern of human behavior information and cause numerous researchers' research interests. As is known,the key to travel information mining from the trajectory data is the stay point recognition and semantic annotation.Overcoming the shortcomings on adaptability and resistance to noise exists in existed stay points identification methods, and also combined with the basic characteristics of the taxi GPS data,We proposed a way with an parameter optimization stratage to get the stay points from a single trajectory and the figure shows it really works well, with high precision and strong adaptability on the recall ratio and precision ratio.And then,based on this significant achievements,we applies a refined clustering method based on the clustering radius and frequency parameters and get the POI results.