Pushing and Non-pushing Forward Motion in Crowds: A Systematic Psychological Observation Method for Rating Individual Behavior in Pedestrian Dynamics


  • Ezel Üsten Institute for Advanced Simulation (IAS-7), Forschungszentrum Jülich, Germany
  • Helena Lügering Institute for Advanced Simulation (IAS-7), Forschungszentrum Jülich, Germany
  • Anna Sieben Institute for Advanced Simulation (IAS-7), Forschungszentrum Jülich, Germany




Pushing behavior impairs people’s sense of well-being in a crowd and represents a significant safety risk. There are nevertheless still a lot of unanswered questions about who behaves how in a crowded situation, and when, where, and why pushing behavior occurs. Beginning from the supposition that a crowd is not thoroughly homogenous and that behavior can change over time, we developed a method to observe and rate forward motion. Based on the guidelines of quantitative content analysis, we came up with four categories: (1) falling behind, (2) just walking, (3) mild pushing, and (4) strong pushing. These categories allow for the classification of the behavior of any person at any time in a video, and thereby the method allows for a comprehensive systematization of individuals’ actions alongside temporal crowd dynamics. The application of this method involves videos of moving crowds including trajectories. The initial results show a very good inter-coder reliability between two trained raters demonstrating the general suitability of the system to describe forward motion in crowds systematically and quantify it for further analysis. In this way, pushing behavior can be better understood and, prospectively, risks better identified. This article offers a comprehensive presentation of this method of observation.


Filingeri, V., Eason, K., Waterson, P., Haslam, R.: Factors influencing experience in crowds - the participant perspective. Applied Ergonomics 59, 431–441 (2017). doi:10.1016/j.apergo.2016.09.009

Adrian, J., Seyfried, A., Sieben, A.: Crowds in front of bottlenecks at entrances from the perspective of physics and social psychology. Journal of the Royal Society Interface 17, 20190871 (2020). doi:10.1098/rsif.2019.0871

Haghani, M., Sarvi, M., Shahhoseini, Z.: When ‘push’ does not come to ‘shove’: Revisiting ‘faster is slower’ in collective egress of human crowds. Transportation Research Part A: Policy and Practice 122, 51–69 (2019). doi:10.1016/j.tra.2019.02.007

Johnson, N.: Panic at “the who concert stampede”: An empirical assessment. Social Problems 34, 362–373 (1987). doi:10.2307/800813

Cocking, C., Drury, J., Reicher, S.: The psychology of crowd behaviour in emergency evacuations: Results from two interview studies and implications for the fire and rescue services. Irish Journal of Psychology 30, 59-73 (2009). doi:10.1080/03033910.2009.10446298

Drury, J., Cocking, C., Reicher, S.: Everyone for themselves? a comparative study of crowd solidarity among emergency survivors. British Journal of Social Psychology 48, 487-506 (2009). doi:10.1348/014466608X357893

Clarke, L.: Panic: Myth or reality? Contexts 1, 21-26 (2002). doi:10.1525/CTX.2002.1.3.21

Helbing, D., Farkas, I.J., Molnár, P., Vicsek, T.: Simulation of pedestrian crowds in normal and evacuation situations. In: Schreckenberg, M., Sharma, S.D. (eds.) Pedestrian and Evacuation Dynamics, pp. 21-58. Springer (2002)

Henein, C.M., White, T.: Agent-based modelling of forces in crowds. In: International Workshop on Multi-Agent Systems and Agent-Based Simulation, pp. 173-184. Springer (2004)

Kim, S., Guy, S., Hillesland, K., Zafar, B., Gutub, A.A., Manocha, D.: Velocity-based modeling of physical interactions in dense crowds. Vis Comput 31, 541–555 (2015). doi:10.1007/s00371-014-0946-1

Sieben, A., Schumann, J., Seyfried, A.: Collective phenomena in crowds—where pedestrian dynamics need social psychology. Plos One 12, 0177328 (2017). doi:10.1371/journal.pone.0177328

Garcimartín, A., Zuriguel, I., Pastor, J., Martín-Gómez, C., Parisi, D.: Experimental evidence of the “faster is slower” effect. Transportation Research Procedia 2, 760–767 (2014). doi:10.1016/J.TRPRO.2014.09.085

Helbing, D., Farkas, I., Vicsek, T.: Simulating dynamical features of escape panic. Nature 407, 487–490 (2000). doi:10.1038/35035023

Drury, J., Cocking, C., Reicher, S., Burton, A., Schofield, D., Hardwick, A., Graham, D., Langston, P.: Cooperation versus competition in a mass emergency evacuation: A new laboratory simulation and a new theoretical model. Behavior Research Methods 41, 957-970 (2009). doi:10.3758/BRM.41.3.957

Mann, L.: Queue culture: The waiting line as a social system. American Journal of Sociology 75, 340-354 (1969). URL https://www.jstor.org/stable/2775696

Schmitt, B.H., Dubé, L., Leclerc, F.: Intrusions into waiting lines: Does the queue constitute a social system? Journal of Personality and Social Psychology 63, 806-815 (1992). doi:10.1037/0022-3514.63.5.806

Cambridge dictionary | push (n.d). Retrieved February 1, 2022, from https://dictionary.cambridge.org/de/worterbuch/englisch/push.

Helbing, D., Mukerji, P.: Crowd disasters as systemic failures: analysis of the love parade disaster. EPJ Data Science 1 (2012). doi:10.1140/epjds7

Neuendorf, K.: The content analysis guidebook, 2nd edn. SAGE Publications (2017)

Döring, N., Bortz, J.: Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften, 5th edn. Springer (2016)

Institute for Advanced Simulation 7: Civil Safety Research, Forschungszentrum Jülich: Data archive of experimental data from studies about pedestrian dynamics [data archive] (n.d.). URL https://ped.fz-juelich.de/da

Boltes, M., Seyfried, A., Steffen, B., Schadschneider, A.: Automatic extraction of pedestrian trajectories from video recordings. In: Klingsch, W., Rogsch, C., Schadschneider, A., Schreckenberg, M. (eds.) Pedestrian and Evacuation Dynamics 2008, p. 43–54. Springer (2010)

Institute for Advanced Simulation 7: Civil Safety Research, Forschungszentrum Jülich: Entrance 2, entry with guiding barriers (corridor setup) [data set] (2013). doi:10.34735/ped.2013.1

Institute for Advanced Simulation 7: Civil Safety Research, Forschungszentrum Jülich: Entrance 1, entry without guiding barriers (semicircle setup) [data set] (2013). doi:10.34735/ped.2013.2

Institute for Advanced Simulation 7: Civil Safety Research, Forschungszentrum Jülich: Crowds in front of bottlenecks from the perspective of physics and social psychology [data set] (2018). doi:10.34735/ped.2018.1

Krippendorff, K.: Computing krippendorff's alpha-reliability (2011). Retrieved from https://repository.upenn.edu/asc_papers/43.

Hayes, A., Krippendorff, K.: Answering the call for a standard reliability measure for coding data. Communication Methods and Measures 1, 77–89 (2007). doi:10.1080/19312450709336664

De Swert, K.: Calculating inter-coder reliability in media content analysis using Krippendorff’s Alpha. Center for Politics and Communication (2012)

Kemloh Wagoum, A., Chraibi, M., Lämmel, G.: Jupedsim: An open framework for simulating and analyzing the dynamics of pedestrians. In: 3rd Conference of the Transportation Research Group of India (2015). URL https://www.researchgate.net/publication/ 289377829_JuPedSim_an_open_framework_for_simulating_ and_analyzing_the_dynamics_of_pedestrians

Alia, A., Maree, M., Chraibi, M.: A hybrid deep learning and visualization framework for pushing behavior detection in pedestrian dynamics. Sensors 22, 4040 (2022). doi:10.3390/s22114040

Alia, A., Maree, M., Haensel, D., Chraibi, M., Lügering, H., Sieben, A., Üsten, E.: Two methods for detecting pushing behavior from videos: A psychological rating system and a deep learning-based crowd behavior analysis. In: Proceedings of the 10th International Conference on Pedestrian and Evacuation Dynamics (PED2021), Paper No. 62 (2021). URL https://drive.google.com/file/d/1OdQIxcxaoCuQJUjQE4AC0NJ_qzC4mVHH/view




How to Cite

Üsten, E., Lügering, H., & Sieben, A. (2022). Pushing and Non-pushing Forward Motion in Crowds: A Systematic Psychological Observation Method for Rating Individual Behavior in Pedestrian Dynamics. Collective Dynamics, 7, 1–16. https://doi.org/10.17815/CD.2022.138