Modeling gap seeking behaviors for agent-based crowd simulation

Research on agent-based crowd simulation has gained tremendous momentum in recent years due to the increase of computing power. One key issue in this research area is to develop various behavioral models to capture the microscopic behaviors of individuals (i.e., agents) in a crowd. In this paper, we propose a novel behavior model for modeling the gap seeking behavior which can be frequently observed in real world scenarios where an individual in a crowd proactively seek for gaps in the crowd flow so as to minimize potential collision with other people. We propose a two-level modeling framework and introduce a gap seeking behavior model as a proactive conflict minimization maneuver at global navigation level. The model is integrated with the reactive collision avoidance model at local steering level. We evaluate our model by simulating a real world scenario. The results show that our model can generate more realistic crowd behaviors compared to the classical social-force model in the given scenario

A Hybridized Approach to Validation: The Role of Sociological Research Methods in Pedestrian Modeling

AbstractPedestrian and crowd-movement models are difficult to validate using traditional empirical methods because of data-related issues such as generalizability, collection ethics, and costs. Commonly used validation methods make strong assumptions about emergence and the importance of crowd structure, leaving a gap in validation literature. The paper reviews the most common methods of validating pedestrian models and proposes a hybridized qualitative approach to validating models that covers more complex group dynamics and possible situations of panic

Panic That Spreads Sociobehavioral Contagion in Pedestrian Evacuations

Crowds are a part of everyday public life, from stadiums and arenas to school hallways. Occasionally, pushing within the crowd spontaneously escalates to crushing behavior, resulting in injuries and even death. The rarity and unpredictability of these incidents provides few options to collect data for research on the prediction and prevention of hazardous emergent behaviors in crowds. This study takes a close look at the way states of agitation, such as panic, can spread through crowds. Group composition—mainly family groups composed of members with differing mobility levels—plays an important role in the spread of agitation through the crowd, ultimately affecting the exit density and evacuation clearance time of a simulated venue. This study used an agent-based model of pedestrian movement during the egress of a hypothetical room and adopted an emotional, cognitive, and social framework to explore the transference and dissipation of agitation through a crowd. The preliminary results reveal that average group size in a crowd is a primary contributor to the exit density and evacuation clearance time. The study provides the groundwork on which to build more elaborate models that incorporate sociobehavioral aspects to simulate human movement during panic situations and account for the potential for dangerous behavior to emerge in crowds