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Eliminating bias in pedestrian density estimation: A Voronoi cell perspective

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  • Mullick, Pratik
  • Appert-Rolland, Cécile
  • Warren, William H.
  • Pettré, Julien

Abstract

For pedestrians moving without spatial constraints, extensive research has been devoted to develop methods of density estimation. In this paper we present a new approach based on Voronoi cells, offering a means to estimate density for individuals in small, unbounded pedestrian groups. A thorough evaluation of existing methods, encompassing both Lagrangian and Eulerian approaches employed in similar contexts, reveals notable limitations. Specifically, these methods turn out to be ill-defined for realistic density estimation along a pedestrian’s trajectory, exhibiting systematic biases and fluctuations that depend on the choice of parameters. There is thus a need for a parameter-independent method to eliminate this bias. We propose a modification of the widely used Voronoi-cell based density estimate to accommodate pedestrian groups, irrespective of their size. The advantages of this modified Voronoi method are that it is an instantaneous method that requires only knowledge of the pedestrians’ positions at a give time, does not depend on the choice of parameter values, gives us a realistic estimate of density in an individual’s neighborhood, and has appropriate physical meaning for both small and large human crowds in a wide variety of situations. We conclude with general remarks about the meaning of density measurements for small groups of pedestrians.

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  • Mullick, Pratik & Appert-Rolland, Cécile & Warren, William H. & Pettré, Julien, 2025. "Eliminating bias in pedestrian density estimation: A Voronoi cell perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 657(C).
  • Handle: RePEc:eee:phsmap:v:657:y:2025:i:c:s037843712400760x
    DOI: 10.1016/j.physa.2024.130251
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    as
    1. Fang, Shuyi & Jin, Cheng-Jie & Jiang, Rui & Li, Dawei, 2024. "Simulating the bi-directional pedestrian flow under high densities by a floor field cellular automaton model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    2. Huang, Lida & Chen, Tao & Wang, Yan & Yuan, Hongyong, 2015. "Congestion detection of pedestrians using the velocity entropy: A case study of Love Parade 2010 disaster," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 440(C), pages 200-209.
    3. Wang, Guanning & Chen, Tao & Zheng, Huijie & Wang, Jianyu & Hu, Xiangmin & Deng, Kaifeng & Tao, Zhenxiang & Luo, Ning, 2023. "Heterogeneous crowd dynamics considering the impact of personality traits under a fire emergency: A questionnaire & simulation-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    4. Lian, Liping & Ye, Rui & Xia, Long & Song, Weiguo & Zhang, Jun & Li, Xiaolian, 2022. "Pedestrian dynamics in single-file merging flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    5. Haghani, Milad, 2021. "The knowledge domain of crowd dynamics: Anatomy of the field, pioneering studies, temporal trends, influential entities and outside-domain impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    6. Nagao, Koki & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2018. "Estimation of crowd density applying wavelet transform and machine learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 145-163.
    7. Li, Yang & Chen, Maoyin & Dou, Zhan & Zheng, Xiaoping & Cheng, Yuan & Mebarki, Ahmed, 2019. "A review of cellular automata models for crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    8. Mavrodiev, Pavlin & Schweitzer, Frank, 2021. "The ambigous role of social influence on the wisdom of crowds: An analytic approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    9. Vincenz Frey & Arnout van de Rijt, 2021. "Social Influence Undermines the Wisdom of the Crowd in Sequential Decision Making," Management Science, INFORMS, vol. 67(7), pages 4273-4286, July.
    10. Cristiani, E. & Menci, M. & Malagnino, A. & Amaro, G.G., 2023. "An all-densities pedestrian simulator based on a dynamic evaluation of the interpersonal distances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).
    11. Nagatani, Takashi, 2002. "Dynamical transition in merging pedestrian flow without bottleneck," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 307(3), pages 505-515.
    12. Wang, Chongyang & Ni, Shunjiang & Weng, Wenguo, 2019. "Modeling human domino process based on interactions among individuals for understanding crowd disasters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    13. Tajima, Yusuke & Nagatani, Takashi, 2002. "Clogging transition of pedestrian flow in T-shaped channel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 239-250.
    14. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
    15. Paetzke, Sarah & Boltes, Maik & Seyfried, Armin, 2022. "Influence of individual factors on fundamental diagrams of pedestrians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    16. Zhang, Dawei & Zhu, Haitao & Hostikka, Simo & Qiu, Shi, 2019. "Pedestrian dynamics in a heterogeneous bidirectional flow: Overtaking behaviour and lane formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 72-84.
    17. Pratik Mullick & Sylvain Fontaine & Cécile Appert-Rolland & Anne-Hélène Olivier & William H Warren & Julien Pettré, 2022. "Analysis of emergent patterns in crossing flows of pedestrians reveals an invariant of ‘stripe’ formation in human data," PLOS Computational Biology, Public Library of Science, vol. 18(6), pages 1-33, June.
    18. Syed, Ahmed & Thampi, Sumesh P. & Panchagnula, Mahesh V., 2022. "Order-stampede transitions in human crowds: The role of individualistic and cooperative forces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    19. Wang, Litao & Shen, Shifei, 2019. "A decay model for the fundamental diagram of pedestrian movement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    20. Guo, Wei & Wang, Xiaolu & Zheng, Xiaoping, 2015. "Lane formation in pedestrian counterflows driven by a potential field considering following and avoidance behaviours," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 87-101.
    21. Bodrova, Anna S. & Najim, Fatema Al & Brilliantov, N.V., 2024. "Lane formation in an active particle model with chirality for pedestrian traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    22. Guo, Ren-Yong & Wong, S.C. & Huang, Hai-Jun & Zhang, Peng & Lam, William H.K., 2010. "A microscopic pedestrian-simulation model and its application to intersecting flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 515-526.
    23. Duives, Dorine C. & Daamen, Winnie & Hoogendoorn, Serge P., 2015. "Quantification of the level of crowdedness for pedestrian movements," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 162-180.
    24. Haghani, Milad & Sarvi, Majid, 2018. "Crowd behaviour and motion: Empirical methods," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 253-294.
    25. Liu, Yixue & Mao, Zhanli, 2022. "An experimental study on the critical state of herd behavior in decision-making of the crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    26. Liu, Yulu & Ma, Xuechen & Tao, Yizhou & Dong, Liyun & Ding, Xu & Qiu, Xiang, 2024. "Numerical investigation on the impact of obstacles on phase transition in pedestrian counter-flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    27. Zeng, Tian & Wei, Yidong & Hu, Zuoan & Ma, Yi, 2023. "Comparison study in single-file pedestrian flow dynamics: Foot motion perspective versus head motion perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    28. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    29. Muramatsu, Masakuni & Nagatani, Takashi, 2000. "Jamming transition in two-dimensional pedestrian traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 275(1), pages 281-291.
    30. Chen, Juan & Luo, Qian & Wang, Qiao & Lo, Jacqueline T.Y. & Ma, Jian, 2024. "Experimental study on individual and crowd movement features around obstacles with different shape and size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).
    31. Bode, Nikolai W.F. & Chraibi, Mohcine & Holl, Stefan, 2019. "The emergence of macroscopic interactions between intersecting pedestrian streams," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 197-210.
    32. Ma, Yi & Yuen, Richard Kwok Kit & Lee, Eric Wai Ming, 2016. "Effective leadership for crowd evacuation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 333-341.
    33. Steffen, B. & Seyfried, A., 2010. "Methods for measuring pedestrian density, flow, speed and direction with minimal scatter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1902-1910.
    34. Kawaguchi, Riho & Yanagisawa, Daichi & Feliciani, Claudio & Nozaki, Shigeto & Abe, Yukari & Mita, Makiko & Nishinari, Katsuhiro, 2023. "Modeling and controlling congestion caused by a bottleneck in an overcrowded aquarium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    35. Keyvan-Ekbatani, Mehdi & Kouvelas, Anastasios & Papamichail, Ioannis & Papageorgiou, Markos, 2012. "Exploiting the fundamental diagram of urban networks for feedback-based gating," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1393-1403.
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