Going Through, Going Around: A Study on Individual Avoidance of Groups

When avoiding a group, a walker has two possibilities: either he goes through it or around it. Going through very dense groups or around huge ones would not seem natural and could break any sense of presence in a virtual environment. This paper aims to enable crowd simulators to handle such situations correctly. To this end, we need to understand how real humans decide to go through or around groups. As a first hypothesis, we apply the Principle of Minimum Energy (PME) on different group sizes and density. According to this principle, a walker should go around small and dense groups whereas he should go through large and sparse groups. Such principle has already been used for crowd simulation; the novelty here is to apply it to decide on a global avoidance strategy instead of local adaptations only. Our study quantifies decision thresholds. However, PME leaves some inconclusive situations for which the two solutions paths have similar energetic costs. In a second part, we propose an experiment to corroborate PME decisions thresholds with real observations. As controlling the factors of an experiment with many people is extremely hard, we propose to use Virtual Reality as a new method to observe human behavior. This work represents the first crowd simulation algorithm component directly designed from a VR-based study. We also consider the role of secondary factors in inconclusive situations. We show the influence of the group appearance and direction of relative motion in the decision process. Finally, we draw some guidelines to integrate our conclusions to existing crowd simulators and show an example of such integration. We evaluate the achieved improvements.

1 Introduction

Virtual reality technologies are constantly evolving to render more and more realistic immersive environments. Realistic environments, such as cities or public buildings, need virtual populations to resemble real ones. Crowd simulators are available to animate populations in virtual environments. Among existing techniques, microscopic approaches provide the highest level of realism for virtual environment applications. They simulate each agent as well as the interactions they have together or with the user. However, solutions generally consider interactions between individual agents only, whereas it has been shown that pedestrian are more often walking in small groups than alone [1]. One reason for the absence of groups in simulators is that local interactions involving groups are not fully understood, and thus, not captured by numerical models of local interactions.