Trajectory Similarity of Network Constrained Moving Objects and Applications to Traffic Security

Spatio-Temporal data analysis plays a central role in many security-related applications including those relevant to transportation infrastructure, border and inland security. In several applications, data objects move on pre-defined spatial networks such as road segments, railways, and invisible air routes, which provides the possibility of representing the data in reduced dimension. This dimensionality reduction gives additional advantages in spatio-temporal data management like indexing, query processing, similarity and clustering of trajectory data etc. There are many proposals concerning trajectory similarity problem which includes Euclidian, network, time based measures and concepts known as Position of Interest(POI), Time of Interest(TOI) etc. This paper demonstrates how these POI and TOI methods could be advantages in security informatics domain suitable to work with road network constrained moving object data, stored using a binary encoding scheme proposed in a previous PAISI paper.