WeLehmberg, DanielDietrich, FelixKevrekidis, Ioannis G.Bungartz, Hans-JoachimKöster, Gerta apply the Koopman operatorKoopman operator framework to pedestrian dynamicsPedestrian dynamics. In an example scenario, we generate crowd density time series data with a microscopic pedestrian simulator. We then approximate the Koopman operatorKoopman operator in matrix form through Extended Dynamic Mode Decomposition, using Geometric Harmonics on the data as a dictionary. The Koopman matrix is integrated into a surrogate modelSurrogate model, which allows to approximate crowd density time series data to be generated, independently from the original microscopic simulator. The evaluation of the constructed surrogate modelSurrogate model is orders of magnitude faster, and enables us to use methods that require many model evaluations.


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    Title :

    Exploring Koopman Operator Based Surrogate Models—Accelerating the Analysis of Critical Pedestrian Densities


    Additional title:

    Springer Proceedings Phys.



    Published in:

    Traffic and Granular Flow 2019 ; Chapter : 19 ; 149-157


    Publication date :

    2020-11-17


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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