Optimization-based pedestrian model calibration for evaluation

David Wolinski, Stephen J. Guy, Anne Hélène Olivier, Ming C. Lin, Dinesh Manocha, Julien Pettré

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

The evaluation and comparison of crowd simulation algorithms (complex, high-dimensional, multi-scale systems) is an important question. "Realism" being dependent on target applications, comparisons with real measurements are not easy. Promising so- lutions have been suggested for such evaluations (Guy et al. (2012)). Here, we address estimating simulation parameters before evaluating: what do evaluation results mean if the assessed model is not performing at its best? We propose an optimization-based approach encompassing: reference data, metrics, simulation algorithms and optimization techniques. We demonstrate finding good parameter values setting simulation results as close as possible to reference data, enabling fair and meaningful comparisons.

Original languageEnglish (US)
Title of host publicationTransportation Research Procedia
PublisherElsevier
Pages228-236
Number of pages9
Volume2
DOIs
StatePublished - 2014

Keywords

  • crowd simulation
  • evaluation
  • ground-truth data
  • optimization
  • parameter estimation

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    Wolinski, D., Guy, S. J., Olivier, A. H., Lin, M. C., Manocha, D., & Pettré, J. (2014). Optimization-based pedestrian model calibration for evaluation. In Transportation Research Procedia (Vol. 2, pp. 228-236). Elsevier. https://doi.org/10.1016/j.trpro.2014.09.041