Diversified Crowd Evacuation Method in Large Public Places

Abstract

Realistic crowd simulation is an important issue for crowd management, public space design, and architectural and urban planning. In this paper, we present a novel approach for planning and directing heterogeneous large-scale crowd in public places. We firstly extract group features from real-world video, and transfer them to the virtual crowd members. On this basis, we perform the crowd evacuation by combining the global path planning and collide avoidance strategy. Our method efficiently produces the most promising paths in both time and space and offers a reasonable distribution of the crowd' members over these paths such that their average evacuation time is minimized based on the probabilistic roadmaps approach. The generated paths are combined with reciprocal velocity obstacle method to handle collisions and generate the final motions of the individuals. We demonstrate its potential on large public places with 10000 individuals and evaluate the results from our simulations using some quantitative quality metrics. In practice, our method can interactively simulate large crowds with thousands of individuals on a desktop PC and naturally generates a diverse set of emergent behaviors.

An improved optimization model for crowd evacuation considering individual exit choice preference

“…An improved social force model was developed to model individual dynamic evacuation behaviors, characterize the complex psychological and physical interaction, and reproduce various self‐organizing crowd phenomena. In a complex geographic scenario with obstacles, such as tall buildings, modeling pedestrian movement entails addressing different aspects of individuals' behaviors, where global route planning and local obstacle avoidance are the vital components (Liu & Lyu, 2019). Thus, the A* algorithm and covering roadmap approach (Snape et al, 2011) were introduced to the primary social force model to guarantee a more realistic evacuation performance without oscillations.…”

3D Indoor Environment Abstraction for Crowd Simulations in Complex Buildings

“…Using a social force model for 3D evacuation of buildings was investigated, testing relatively simple building layouts coming from CityGML LOD4 models [10]. A method performing crowd simulations in large public spaces is suggested modelling interactions between thousands of agents [9]. However, the inability to consider small objects and multi-floor environments are suggested limitations of the study.…”

“…Although continuous models are computationally the most demanding, the recent advancement in the processing power of computers allows their use without much difficulty. The main challenge that persists is the inability to use any building model coming from different sources, but rather simple models with well-defined geometrical and property-rich structures [9,10]. Regarding crowd simulation models, seven methodological approaches including cellular automata, social force, lattice gas, fluid dynamics, agent-based, game theories and approaches based on experiments with animals are identified [11].…”

Dense crowd detection method based on improved YOLOv7

“…A dense crowd refers to a high-density gathering of people in a confined space, where the density reaches a certain level and the risk of aggregation approaches a critical threshold. Its characteristics are as follows: 1) Non-adaptability [1]. In emergency situations, fear spreads rapidly within a dense crowd, leading to intensified conformity and competition among individuals, ultimately resulting in stampedes.…”