Asymmetries in Group-Individual Collision Avoidance due to Social Factors


  • Adrien Gregorj Okayama University, Okayama, Japan
  • Zeynep Yücel Okayama University, Okayama, Japan; Advanced Telecommunication Research Institute International, Kyoto, Japan
  • Francesco Zanlungo Okayama University, Okayama, Japan; Advanced Telecommunication Research Institute International, Kyoto, Japan; Osaka International Professional University, Osaka, Japan
  • Takayuki Kanda Advanced Telecommunication Research Institute International, Kyoto, Japan; Kyoto University, Kyoto, Japan



Microscopic pedestrian dynamics, Social groups, Collision avoidance


This research centers on analyzing frontal encounters between dyads (two-person groups) and individuals, aiming to measure each participant's role in avoiding collisions based on their deviation from their intended path. To achieve this, we establish the intended trajectory of each party by taking into account their walking direction leading up to the encounter. The largest discrepancy between this intended path and the observed path can be interpreted as the pedestrian's maximum lateral deviation.
We show a noteworthy discrepancy in deviation between group members and individuals in face-to-face encounters. Furthermore, we conduct an in-depth analysis of how the intensity of interaction among group members impacts collision avoidance dynamics. Notably, the contrast in deviation between individuals and group members is most pronounced when the level of interaction within the group is high. Ultimately, our findings consistently indicate that higher levels of interaction lead to more substantial deviations in the trajectories of encountered individuals and underscore the significant role of social dynamics in influencing pedestrian behavior during frontal encounters.


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How to Cite

Gregorj, A., Yücel, Z., Zanlungo, F., & Kanda, T. (2024). Asymmetries in Group-Individual Collision Avoidance due to Social Factors. Collective Dynamics, 9, 1–9.



Special Issue of Pedestrian and Evacuation Dynamics 2023