Towards an Integrated Approach to Crowd Analysis and Crowd Synthesis: a Case Study and First Results

Abstract

Studies related to crowds of pedestrians, both those of theoretical nature and application oriented ones, have generally focused on either the analysis or the synthesis of the phenomena related to the interplay between individual pedestrians, each characterised by goals, preferences and potentially relevant relationships with others, and the environment in which they are situated. The cases in which these activities have been systematically integrated for a mutual benefit are still very few compared to the corpus of crowd related literature. This paper presents a case study of an integrated approach to the definition of an innovative model for pedestrian and crowd simulation (on the side of synthesis) that was actually motivated and supported by the analyses of empirical data acquired from both experimental settings and observations in real world scenarios. In particular, we will introduce a model for the adaptive behaviour of pedestrians that are also members of groups, that strive to maintain their cohesion even in difficult (e.g. high density) situations. The paper will show how the synthesis phase also provided inputs to the analysis of empirical data, in a virtuous circle.

Preprint submitted to Pattern Recognition Letters March 20, 2013

References in corpus (4)

• Transitions in pedestrian fundamental diagrams of straight corridors and T-junctions
• Extended floor field CA model for evacuation dynamics
• Group dynamic behavior and psychometric profiles as substantial driver for pedestrian dynamics
• Empirical study of turning and merging of pedestrian streams in T-junction

Cited by in corpus (7)

• A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density Estimation
• Generative Adversarial Networks for Spatio-temporal Data: A Survey
• Micro and Macro Pedestrian Dynamics in Counterflow: the Impact of Social Groups
• Detecting socially interacting groups using f-formation: A survey of taxonomy, methods, datasets, applications, challenges, and future research directions
• GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds
• Essentials of an Integrated Crowd Management Support System Based on Collective Artificial Intelligence
• Socially Constrained Structural Learning for Groups Detection in Crowd