Agent-based simulations can be helpful in understanding the complex dynamics of human behavior. Data-driven approaches for this purpose show to be promising in extracting complex features, without relying on system-specific expert knowledge. This work aims to develop a data-driven approach that enables automatic generation of agent-based pedestrian flow models, by extracting and classifying regions of interest from trajectory data. For validation purposes, synthetic data from a pedestrian movement simulation was used for the method development. We identify stay point areas from the resulting trajectories, classify the processes occurring in these areas, and reconstruct their properties. The relevant areas and types of processes were successfully extracted in four different case scenarios. However, it is necessary to test and subsequently improve these methods by using real data. Ultimately, our methods should be applied for the automatic modeling of pedestrian behavior in critical infrastructures, such as a railway station or an airport.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Data-Driven Reconstruction of Processes From Pedestrian Trajectories


    Contributors:


    Publication date :

    2024-05-20


    Size :

    1711371 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Comparison of pedestrian accident reconstruction models to experimental test data for wrap trajectories

    Fugger, T. F. / Randles, B. C. / Eubanks, J. J. et al. | British Library Conference Proceedings | 2000


    Comparison of pedestrian accident reconstruction models to experimental test data for wrap trajectories

    Fugger,T.F. / Randles,B.C. / Eubanks,J.J. et al. | Automotive engineering | 2000


    Pedestrian accident reconstruction

    Eubanks, Jerry J. | TIBKAT | 1994



    Data-driven modeling of pedestrian crowds

    Johansson, Anders Fredrik | SLUB | 2009