Group spatiotemporal pattern queries

Reporting the motion patterns in moving objects data has been the focus of many research projects recently. Group spatiotemporal patterns are the movement patterns, in space and time, formed by groups of moving objects, such as flocks, concurrence, encounter, etc. There exist, in the literature, smart algorithms for matching some of these patterns. These solutions, however, address specific patterns and require specialized data representation and indexes. They share too little to be integrated into a single system. There is a need for a generic query method. In this paper, we propose a language that can consistently express and evaluate a wide range of group spatiotemporal pattern queries. We formally define the language operators, illustrate the evaluation algorithms, and discuss the optimization methods. Several examples are given to showcase the expressive power of the language.