Prof. Dr.

Wrobel, Stefan

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  • Publication
    Pedestrian quantity estimation with trajectory patterns
    ( 2012)
    Liebig, Thomas
    ;
    Xu, Zhao
    ;
    May, Michael
    ;
    Wrobel, Stefan
    In street-based mobility mining, traffic volume estimation receives increasing attention as it provides important applications such as emergency support systems, quality-of-service evaluation and billboard placement. In many real world scenarios, empirical measurements are usually sparse due to some constraints. On the other hand, pedestrians generally show some movement preferences, especially in closed environments, e.g., train stations. We propose a Gaussian process regression based method for traffic volume estimation, which incorporates topological information and prior knowledge on preferred trajectories with a trajectory pattern kernel. Our approach also enables effectively finding most informative sensor placements. We evaluate our method with synthetic German train station pedestr ian data and real-world episodic movement data from the zoo of Duisburg. The empirical analysis demonstrates that incorporating trajectory patterns can largely improve the traffic prediction accuracy, especially when traffic networks are sparsely monitored.
  • Publication
    Visit potential: A common vocabulary for the analysis of entity-location interactions in mobility applications
    ( 2010)
    Körner, Christine
    ;
    Hecker, Dirk
    ;
    May, Michael
    ;
    Wrobel, Stefan
    A growing number of companies and public institutions use mobility data in their day-to-day business. One type of usage is the analysis of spatio-temporal interactions between mobile entities and geographic locations. In practice the employed measures depend on application demands and use context-specific terminology. Thus, a patchwork of measures has evolved which is not suitable for methodological research and interdisciplinary ex-change of ideas. The measures lack a systematic formalization and a uni-form terminology. In this paper we therefore systematically define meas-ures for entity-location interactions which we name visit potential. We provide a common vocabulary that can be applied for an entire class of mobility applications. We present two real-world scenarios which apply entity-location interaction measures and demonstrate how the employed measures can be precisely defined in terms of visit potential.