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A microscopic method for the evaluating of continuous pedestrian dynamic models

Author

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  • Huang, Zhongyi
  • Chraibi, Mohcine
  • Cao, Shuchao
  • Huang, Chuanli
  • Fang, Zhiming
  • Song, Weiguo

Abstract

In this paper, we propose a microscopic method to evaluate continuous pedestrian dynamic models at the trajectory level. By comparing the experimental and the simulated trajectory in four directions, the evaluation of the model can be described by a radar chart, with which both qualitative and quantitative conclusions can be obtained. In order to demonstrate our method, we evaluate a social force model by 1,936 trajectories with graded densities in three different scenarios. Three qualitative conclusions are obtained by observing radar charts of the simulation of the unidirectional experiments. All of them are verified by the comparison of the macroscopic parameters. Besides, we find that a model with smaller error in our method always has a better performance at the macroscopic level. At last, the possible quantitative descriptions of the method are discussed. Compared to the evaluations by comparing collective features like fundamental diagram, our method is general, comprehensive and quantitative. The method provides a new possibility to evaluate any continuous pedestrian dynamic model in any scenario with a standard process.

Suggested Citation

  • Huang, Zhongyi & Chraibi, Mohcine & Cao, Shuchao & Huang, Chuanli & Fang, Zhiming & Song, Weiguo, 2019. "A microscopic method for the evaluating of continuous pedestrian dynamic models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119314141
    DOI: 10.1016/j.physa.2019.122461
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    References listed on IDEAS

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    1. Ma, Jian & Song, Wei-guo & Zhang, Jun & Lo, Siu-ming & Liao, Guang-xuan, 2010. "k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2101-2117.
    2. Anders Johansson & Dirk Helbing & Pradyumn K. Shukla, 2007. "Specification Of The Social Force Pedestrian Model By Evolutionary Adjustment To Video Tracking Data," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(supp0), pages 271-288.
    3. von Sivers, Isabella & Köster, Gerta, 2015. "Dynamic stride length adaptation according to utility and personal space," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 104-117.
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    5. Parisi, Daniel R. & Gilman, Marcelo & Moldovan, Herman, 2009. "A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3600-3608.
    6. Cao, Shuchao & Song, Weiguo & Lv, Wei & Fang, Zhiming, 2015. "A multi-grid model for pedestrian evacuation in a room without visibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 45-61.
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