Spatio-Temporal Similarity Analysis between Trajectories on Road Networks Jung-Rae Hwang 1 , Hye-Young Kang 2 , and Ki-Joune Li 2 1 Department of Geographic Information Systems, Pusan National University, Korea 2 Department of Computer Science, Pusan National University, Korea {jrhwang,hykang}@isel.cs.pusan.ac.kr, lik@pnu.edu Abstract. In order to analyze the behavior of moving objects, a mea- sure for determining the similarity of trajectories needs to be defined. Although research has been conducted that retrieved similar trajecto- ries of moving objects in Euclidean space, very little research has been conducted on moving objects in the space defined by road networks. In terms of real applications, most moving objects are located in road net- work space rather than in Euclidean space. In this paper, we investigate the properties of similar trajectories in road network space. And we pro- pose a method to retrieve similar trajectories based on this observation and similarity measure between trajectories on road network space. Ex- perimental results show that this method provides not only a practical method for searching for similar trajectories but also a clustering method for trajectories. Keywords: Trajectories, Road Network Space, Similarity between Trajec- tories 1 Introduction With the spread of mobile computing, research to efficiently handle moving objects, where their movement is represented by a trajectory as a set of line segments in (x, y, t) space, has become important [1]. Since the trajectory of a moving object contains a lot of information, it is an interesting task to analyze trajectories for several application areas. One of the most important require- ments for analyzing trajectories is to search for objects with similar trajectories and cluster them. For example, a query such as ”Find all moving objects whose trajectories are similar to a given query trajectory” is typical. While research has been done regarding locating similar trajectories of mov- ing objects on Euclidean space, very little has been done regarding to moving objects in road network space. For most of real applications, we are interested in moving objects in road network space rather than in Euclidean space. In order to analyze the behavior of moving objects in road network space, a measure for determining the similarity between the trajectories of moving objects needs to be defined. This measurement of similarity allows for the retrieval of similar trajectories and the eventual discovery of their patterns and clusters.