In multi-player geogames, players collaborate to solve wayfinding tasks and thereby form groups. The trajectories of these groups can be analyzed using established concepts from the literature (e.g., Gudmundsson, van Kreveld & Speckmann), which distinguish characteristic motion patterns such as Flock (common direction and proximity), Leadership (a subgroup follows a “leader”), Convergence (movement towards the same location), and Encounter (meeting at the same place and time).

At the Institute for Geoinformatics, the location-based game GeoGami (www.geogami.org / https://app.geogami.ifgi.de/ provides the technical framework for multiplayer games and the collection of movement data. Games can be implemented flexibly in real-world outdoor and indoor settings as well as in virtual reality environments, thus generating diverse trajectory datasets.

In this thesis, you will develop and apply methods for comparing group trajectories with respect to similarities in direction, speed, position, and spatial proximity of trajectory points over time intervals. These methods are to be implemented and evaluated using empirical trajectory data from multiplayer geogames.

Gudmundsson, J., van Kreveld, M. & Speckmann, B. Efficient Detection of Patterns in 2D Trajectories of Moving Points. Geoinformatica 11, 195–215 (2007). https://doi.org/10.1007/s10707-006-0002-z

Gudmundsson, J., Laube, P., Wolle, T. (2008). Movement Patterns in Spatio‐temporal Data. In: Shekhar, S., Xiong, H. (eds) Encyclopedia of GIS. Springer, Boston, MA. , pp 726–732, https://doi.org/10.1007/978-0-387-35973-1_823