Abstract
In this work we propose a methodology for assessment of pedestrian models continuous in space. With respect to the Kolmogorov–Smirnov distance between two data-clouds, representing, for instance, simulated and the corresponding empirical data, we calculate an evaluation factor between zero and one. Based on the value of the herein developed factor, we make a statement about the goodness of the model under evaluation. Moreover this process can be repeated in an automatic way in order to maximize the above-mentioned factor and hence determine the optimal set of model parameters.
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Kurtc, V., Chraibi, M., Tordeux, A. (2019). Automated Quality Assessment of Space-Continuous Models for Pedestrian Dynamics. In: Hamdar, S. (eds) Traffic and Granular Flow '17. TGF 2017. Springer, Cham. https://doi.org/10.1007/978-3-030-11440-4_35
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DOI: https://doi.org/10.1007/978-3-030-11440-4_35
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