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Modeling and Simulating Pedestrian Social Group Behavior with Heterogeneous Social Relationships

Manon Prédhumeau 1, 2, 3 Julie Dugdale 1, 2 Anne Spalanzani 1, 3
2 HAwAI - Human Aware Artificial Intelligence
LIG - Laboratoire d'Informatique de Grenoble
3 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : The nature of the social relationship within a pedestrian group influences the group's structure and behavior and thus its entitativity (i.e. the perception of a group as a unit by other pedestrians). However, existing crowd models ignore the diversity of social relationships and have limitations in reproducing group avoidance behaviors. The proposed model is an adaptation of the social force model that addresses group social relationships. The approach is calibrated by comparing the distances and angles between members of the simulated groups with observations in real crowds. Results show that intra-group distances are a key factor in collision avoidance behavior. Simulation of collision avoidance shows that group members behavior fits better with empirical data than the original model and that individuals avoid splitting groups. By simply tuning the distribution of social relationships in the simulated crowd, the model can be used to reproduce crowd behaviors in several contexts.
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https://hal.archives-ouvertes.fr/hal-02514963
Contributor : Manon Prédhumeau <>
Submitted on : Thursday, April 9, 2020 - 10:10:47 AM
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Manon Prédhumeau, Julie Dugdale, Anne Spalanzani. Modeling and Simulating Pedestrian Social Group Behavior with Heterogeneous Social Relationships. SCS 2020 - Spring Simulation Conference, May 2020, Virtual event, United States. ⟨hal-02514963⟩

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