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Spice: a cognitive agent framework for computational crowd simulations in complex environments

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Abstract

Pedestrian behavior is an omnipresent topic, but the underlying cognitive processes and the various influences on movement behavior are still not fully understood. Nonetheless, computational simulations that predict crowd behavior are essential for safety, economics, and transport. Contemporary approaches of pedestrian behavior modeling focus strongly on the movement aspects and seldom address the rich body of research from cognitive science. Similarly, general purpose cognitive architectures are not suitable for agents that can move in spatial domains because they do not consider the profound findings of pedestrian dynamics research. Thus, multi-agent simulations of crowd behavior that strongly incorporate both research domains have not yet been fully realized. Here, we propose the cognitive agent framework Spice. The framework provides an approach to structure pedestrian agent models by integrating concepts of pedestrian dynamics and cognition. Further, we provide a model that implements the framework. The model solves spatial sequential choice problems in sufficient detail, including movement and cognition aspects. We apply the model in a computer simulation and validate the Spice approach by means of data from an uncontrolled field study. The Spice framework is an important starting point for further research, as we believe that fostering interdisciplinary modeling approaches will be highly beneficial to the field of pedestrian dynamics.

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Notes

  1. 1.

    The term scenario defines the virtual environment in which the model is applied. Here, one has to differentiate between the environment and the model, because the model can be applied to diverse scenarios without changing the model’s mathematical features.

  2. 2.

    In pedestrian dynamics, operational models describe movement/walking behavior. Throughout this paper, we will refer to operational models (in pedestrian dynamics sense) as walking or movement models.

  3. 3.

    https://github.com/tumcms/MomenTUM.

  4. 4.

    The tool was provided by Prof. Köster and her team, University of Applied Sciences Munich.

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Acknowledgements

This work was partially supported by the Federal Ministry for Education and Research (Bundesministerium für Bildung und Forschung, BMBF), project MultikOSi, under Grant FKZ 13N12823. We would like to thank Prof. Hölscher, Chair of Cognitive Sciences at the ETH-Zürich and his team for fruitful discussions. Also, we thank our student assistants for contributing to the pedestrian simulation framework MomenTUM.

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Correspondence to Peter M. Kielar.

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Kielar, P.M., Borrmann, A. Spice: a cognitive agent framework for computational crowd simulations in complex environments. Auton Agent Multi-Agent Syst 32, 387–416 (2018). https://doi.org/10.1007/s10458-018-9383-2

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Keywords

  • Spatial sequential choice
  • Cognitive agent
  • Multi-agent simulation
  • Pedestrian dynamics
  • Crowd simulation