Transporting objects by multiagent cooperation in crowd simulation

2018 ◽  
Vol 29 (3-4) ◽  
pp. e1826 ◽  
Author(s):  
Hsuan Chen ◽  
Sai-Keung Wong
Keyword(s):  
Crowd Simulation ◽  
Multiagent Cooperation

Evaluation of Guidance Systems at Dynamic Public Transport Hubs Using Crowd Simulation

2020 ◽  
Author(s):  
Michael Wagner ◽  
Henriette Cornet ◽  
David Eckhoff ◽  
Philipp Andelfinger ◽  
Wentong Cai ◽  
...  
Keyword(s):  
Public Transport ◽  
Crowd Simulation ◽  
Guidance Systems

scholarly journals Sensitivity Analysis for Microscopic Crowd Simulation

Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 162
Author(s):  
Marion Gödel ◽  
Rainer Fischer ◽  
Gerta Köster
Keyword(s):  
Sensitivity Analysis ◽  
Low Cost ◽  
Input Parameter ◽  
Dimensional Subspace ◽  
Crowd Simulation ◽  
Pedestrian Dynamics ◽  
Sensitivity Indices ◽  
Expensive Problems ◽  
Influential Parameters ◽  
Typical Scenario

Microscopic crowd simulation can help to enhance the safety of pedestrians in situations that range from museum visits to music festivals. To obtain a useful prediction, the input parameters must be chosen carefully. In many cases, a lack of knowledge or limited measurement accuracy add uncertainty to the input. In addition, for meaningful parameter studies, we first need to identify the most influential parameters of our parametric computer models. The field of uncertainty quantification offers standardized and fully automatized methods that we believe to be beneficial for pedestrian dynamics. In addition, many methods come at a comparatively low cost, even for computationally expensive problems. This allows for their application to larger scenarios. We aim to identify and adapt fitting methods to microscopic crowd simulation in order to explore their potential in pedestrian dynamics. In this work, we first perform a variance-based sensitivity analysis using Sobol’ indices and then crosscheck the results by a derivative-based measure, the activity scores. We apply both methods to a typical scenario in crowd simulation, a bottleneck. Because constrictions can lead to high crowd densities and delays in evacuations, several experiments and simulation studies have been conducted for this setting. We show qualitative agreement between the results of both methods. Additionally, we identify a one-dimensional subspace in the input parameter space and discuss its impact on the simulation. Moreover, we analyze and interpret the sensitivity indices with respect to the bottleneck scenario.

scholarly journals A history of crowd simulation: the past, evolution, and new perspectives

2021 ◽  
Author(s):  
Soraia Raupp Musse ◽  
Vinicius Jurinic Cassol ◽  
Daniel Thalmann
Keyword(s):  
Crowd Simulation ◽  
The Past ◽  
History Of

scholarly journals Scalable nonlinear dynamical systems for agent steering and crowd simulation

2001 ◽  
Vol 25 (6) ◽  
pp. 983-998 ◽  
Author(s):  
Siome Goldenstein ◽  
Menelaos Karavelas ◽  
Dimitris Metaxas ◽  
Leonidas Guibas ◽  
Eric Aaron ◽  
...  
Keyword(s):  
Dynamical Systems ◽  
Nonlinear Dynamical Systems ◽  
Crowd Simulation ◽  
Nonlinear Dynamical

Behavioral diversity as multiagent cooperation

1999 ◽  
Author(s):  
Tucker Balch
Keyword(s):  
Behavioral Diversity ◽  
Multiagent Cooperation

A Radar-Nearest-Neighbor based data-driven approach for crowd simulation

2021 ◽  
Vol 129 ◽  
pp. 103260
Author(s):  
Xuedan Zhao ◽  
Jun Zhang ◽  
Weiguo Song
Keyword(s):  
Nearest Neighbor ◽  
Crowd Simulation ◽  
Data Driven ◽  
Data Driven Approach

Nonmonotonic Reasoning of Multiagent Cooperation and Dynamic Propositional Control

2009 ◽  
Author(s):  
Xianwei Lai ◽  
Xiuli Wang ◽  
Bixiong Liu ◽  
Zhengyuan Ning
Keyword(s):  
Nonmonotonic Reasoning ◽  
Multiagent Cooperation

scholarly journals Parallel Motion Simulation of Large-Scale Real-Time Crowd in a Hierarchical Environmental Model

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Xin Wang ◽  
Jianhua Zhang ◽  
Massimo Scalia
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Simulation Method ◽  
Crowd Simulation ◽  
Motion Path ◽  
Motion Simulation ◽  
Environmental Model ◽  
Parallel Methods ◽  
Parallel Motion ◽  
Methods Numerical

This paper presents a parallel real-time crowd simulation method based on a hierarchical environmental model. A dynamical model of the complex environment should be constructed to simulate the state transition and propagation of individual motions. By modeling of a virtual environment where virtual crowds reside, we employ different parallel methods on a topological layer, a path layer and a perceptual layer. We propose a parallel motion path matching method based on the path layer and a parallel crowd simulation method based on the perceptual layer. The large-scale real-time crowd simulation becomes possible with these methods. Numerical experiments are carried out to demonstrate the methods and results.

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