EVA – Crowd Modelling/ Dynamics – videos and PDF’s

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The gathering of information, news articles and reports to assist in planning.

“Extreme Value Analysis (EVA) is simply a method of estimating the probability of a rare event. It is perhaps best known for its application in meteorology where it is used to predict the likelihood of extreme weather conditions such as heavy rain maximum frost penetration or extreme wind conditions. The method is also used in engineering to predict the possible failure rate of a mechanical system. A wider application to crowd safety planning was used by Brian Toft (1990) in his thesis, A failure of hindsight, to support his argument that crowd related accidents should not be treated as unavoidable acts of god but more likely a failure of risk analysis.”

Mick Upton

Crowd Dynamics and Emergency Escape in Immersive Virtual Environments

Psychological Parameters for Crowd Simulation

Implicit Crowd Simulation

Barcelona Camp Nou Stadium: multimodal crowd and vehicle modelling with Legion for Aimsun

SmartMove crowd flow modelling of St. Giles Circus London

SmartMove crowd flow modelling to optimize a commercial office campus

SmartMove crowd flow modelling of Cardiff Central Square during a Millennium Stadium event

An anticipatory interaction model for a crowd of pedestrians

Interactive Simulation of Dynamic Crowd Behaviors using General Adaptation Syndrome Theory

Mina to Jamarat Crowd Movement

Crowd-driven Mid-scale Layout Design

Crowd Simulation

Crowd dynamics experiment: Exit choice in an evacuation

Crowd dynamics experiment: Merging crowds during an evacuation

Crowd Modelling using Pathfinder (Squared Room – one exit in the corner, pop. density 2pm2) RMT

Crowd Modelling using Pathfinder (Squared Room – 1 exit in the middle wall pop density 2pm2) RMT

MassMotion Advanced Crowd Simulation Software by Oasys

CrowdIQ – New Project – Crowd Dynamics International Ltd

FEMTC 2011 – The Utility of a Panic Model on Simulating Crowd Disasters

FEMTC 2011 – Evacuation Modeling Dependence on Input Parameters

Aggregate Dynamics for Dense Crowd Simulation

ClearPath: Highly Parallel Collision Avoidance for Multi-agent Simulatio

Directing Crowd Simulations Using Navigation Fields

Interactive Large-scale Crowd Simulation

PLEdestrians: A Least-effort Approach to Crowd Simulation

Real-Time Density-Based Crowd Simulation


Thunderhead Engineering Pathfinder


 Oasys MassMotion

Oasys MassMotion – Bird’s Nest Stadium vs. The Colosseum

Webinar: An Introduction to MassMotion Flow Beta

Crowd Simulation using MassMotion

Oasys MassMotion Tutorial – Create a basic simulation

Oasys Webinar: Creating MassMotion Models – 14th May 2014

MassMotion 4.7 01-action-part-one

MassMotion 4.7 02-action-part-two

MassMotion 4.7 03-evacuate-zones-actions

MassMotion 4.7 04-checkin-part-one-processing

MassMotion 4.7 05-checkin-part-two-actions

Webinar: Setting up MassMotion scenarios with Schedules and Timetables

MassMotion Importing Geometry Tutorial

MassMotion Geometry Editing Tools Tutorial

MassMotion Validation and Simulation Tutorial

MassMotion Agent Actions Tutorial

MassMotion Analysis Tutorial

MassMotion Process Chains Tutorial

Pedestrian Dynamics


Event Crowd Simulation with Pedestrian Dynamics

Crowd flow simulation of bomb impact in stadium

Crowd flows simulation of fire on tribune stands

Crowd flow simulation of mixed fans in a stadium


Crowd Dynamics PDF links

Crowd Dynamics

G. Keith Still
PhD Thesis
University of Warwick

Pedestrian, Crowd and Evacuation Dynamics


ETH Zurich, Zurich, Switzerland
Institute for Advanced Study, Collegium Budapest,
Budapest, Hungary

Aggregate Dynamics for Dense Crowd Simulation

Rahul Narain   Abhinav Golas   Sean Curtis   Ming C. Lin
University of North Carolina at Chapel Hill

The Dynamics of Crowds

Gareth William Parry

MSc. in Modern Applications of Mathematics

University of Bath

New Models for Crowd Dynamics and Control

Sadeq J. Al-nasur
Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Electrical and Computer Engineering

Continuum Crowds

Adrien Treuille  Seth Cooper  Zoran Popovic

University of Washington

Electronic Arts

Agent-based Crowd Simulation Considering Emotion Contagion for Emergency Evacuation Problem

Hamed Faroqi ,  , Mohammad-Saadi Mesgari

Single-Image Crowd Counting via Multi-Column Convolutional Neural Network

Yingying Zhang Desen Zhou Siqin Chen Shenghua Gao Yi Ma

Shanghaitech University

Crowd-driven Mid-scale Layout Design – DOWNLOAD

Tian Feng,  Lap-Fai Yu,  Sai-Kit Yeung,  KangKang Yin,  Kun Zhou

How do people queue? A study of different queuing models

TGF 2015 Delft, 28th October 2015


Ahmad Zakwan Azizul Fata, Mohd Shafry Mohd Rahim, Sarudin Kari

Modelling large-scale evacuation of music festivals

E. Ronchi,F. Nieto Uriz,X. Criel,P. Reilly

Dynamic Simulation of Virtual Agents and Obstacles in Virtual Cities

Roman Mankovecky´ ∗ Supervised by: Fotis Liarokapis

HCI Lab, Faculty of Informatics Masaryk University Brno / Czech Republic

Velocity-Based Modeling of Physical Interactions in Dense Crowds

Supplementary video: http://youtu.be/KAnmNg2_hI4

Sujeong Kim · Stephen J. Guy · Karl Hillesland · Basim Zafar · Adnan Gutub · Dinesh Manocha

Crowd Art: Density and Flow Based Crowd Motion Design

Kevin Jordao, Panayiotis Charalambous, Marc Christie, Julien Pettr´e, Marie-Paule Cani


Lam Thu BUI and Van Vien MAC

Crowds2D – a new, robust crowd dynamics simulation model

Steinar Børve

A Study of Modeling Crowd Dynamics

Andrew Fell

Carleton University

Modelling Crowd Dynamics During Evacuation Situations Using Simulation

Hugo Winter

Lancaster University

The walking behaviour of pedestrian social groups and its  impact on crowd dynamics

Mehdi Moussaïd   Niriaska Perozo  Simon Garnier  Dirk Helbing  and  Guy Theraulaz

Modelling Crowd dynamics Influence factors related to the probability of a riot

Nanda Wijermans, Ren´e Jorna  Wander Jager  and Tony van Vliet

The Impact of Cultural Differences on Crowd Dynamics in  Pedestrian and Evacuation Domains

Gal Kaminka
Bar Ilan University
Department of Computer Science and Brain Science Center
Computer Science Department
Ramat Gan, Israel 52900


Shigeyuki Okazaki and Satoshi Matsushita

 Human exit route choice in virtual crowd evacuations

The collective behaviour of human crowds emerges from the local interactions of individuals. To understand human crowds we therefore need to identify the behavioural rules individual pedestrians follow.

Discrete choice models of pedestrian walking behaviour

Gianluca Antonini ,Michel Bierlaire , Mats Weber

Dynamic decision making: Human control of complex systems

Berndt Brehmer

Simulation of pedestrian dynamics using a two-dimensional cellular automaton

C. Burstedde, K. Klauck, A. Schadschneider, J. Zittartz

Consensus decision making in human crowds


Leadership and social information use in human crowds

Jolyon J. Faria , John R.G. Dyer a,1, Colin R. Tosh a, Jens Krause

Crossing at a red light: Behaviour of individuals and groups

Tova Rosenbloom

Cellular automaton model for evacuation process with obstacles

A. Varasa, M.D. Cornejoa, D. Mainemera, B. Toledob,, J. Rogana, V. Mun˜ oza, J.A. Valdiviaa

Crowd simulation for dynamic environments based on information spreading and agents’ personal interests

Konrad Jablonski a, Vasileios Argyriou a,, Darrel Greenhill

An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster

Neal Wagner, Vikas Agrawal

A Simple and Realistic Pedestrian Model for Crowd Simulation and Application

Wonho Kang and Youngnam Han

John Prpić  Prashant Shukla

Understanding Collective Crowd Behaviors: Learning a Mixture Model of Dynamic Pedestrian-Agents

Bolei Zhou, Xiaogang Wang, and Xiaoou Tang

Position-Based Multi-Agent Dynamics for Real-Time Crowd Simulation – MiG 2017

Tomer Weiss  Alan Litteneker Chenfanfu Jiang Demetri Terzopoulos

A Model of Human Crowd Behavior: Group Inter-Relationship and Collision Detection Analysis

S. R. Musse and D. Thalmann

On the Mathematical Modeling and Simulation of Crowd Motion

Marie-Therese Wolfram

A Cellular Automaton Model for Crowd Movement and Egress Simulation

Von der Fakulta ̈t 4 – Naturwissenschaften

Creating Crowd Variation with the OCEAN Personality Model (Short Paper)

Funda Durupınar Jan Allbeck Nuria Pelechano Norman Badler

Xiaona Lia, Wenhu Qin

Bayesian Model Adaptation for Crowd Counts

Bo Liu Nuno Vasconcelos

A revolutionary crowd model: Implemented to contrast oscillating to consistent media influence on crowd behavior

Yasser Ibrahim and Rasha Hassan

Towards a Cognitive Model of Crowd Behavior Based on Social Comparison Theory

Natalie Fridman and Gal A. Kaminka

Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions

Dirk Helbing, Lubos Buzna, Anders Johansson, Torsten Werner,

Stephen J. Guy, Jur van den Berg, Wenxi Liu, Rynson Lau, Ming C. Lin, Dinesh Manocha

Dmitriy Rybokonenko, Marina Balakhontceva,

Daniil Voloshin and Vladislav Karbovskii

Counterflow Model for Agent-Based Simulation of Crowd Dynamics

Simo Helio ̈vaaraa, Timo Korhonen, Simo Hostikka, Harri Ehtamo

The Impact of Culture on Crowd Dynamics: An Empirical Approach

Natalie Fridman Gal, A. Kaminka, Avishay Zilka

The walking behaviour of pedestrian social groups and its impact on crowd dynamics

Mehdi Moussaïd, Niriaska Perozo, Simon Garnier, Dirk Helbing, and Guy Theraulaz

Crowd Dynamics and Control in High-Volume Metro Rail


Briane Paul V. Samson , Crisanto R. Aldanese IV , Deanne Moree C.Chan , Jona Joyce S. San Pascual, and Ma. Victoria Angelica P. Sido



Perception of Emotions from Crowd Dynamics

M.W. Baig, Mirza Sulman Baig, V. Bastani, E.I. Barakova, L. Marcenaro, C. S. Regazzoni and M. Rauterberg

On the Mathematical Modeling and Simulation of Crowd Motion

Marie-Therese Wolfram

Mobile ad hoc networks group mobility models of Hajj crowd dynamics

Oussama Mohamed Reda


A Multi-agent Model for Panic Behavior in Crowds

Robson dos Santos Franc ̧a, Maria das Gra ̧cas Bruno Marietto, and Margarethe Born Steinberger

Hidden Markov Models for Optical Flow Analysis in Crowds

Ernesto L. Andrade, Scott Blunsden and Robert B. Fisher

YI, Shuai

Implicit Crowds: Optimization Integrator for Robust Crowd Simulation

IOANNIS KARAMOUZAS, Clemson UniversityNICK SOHRE, University of Minnesota
RAHUL NARAIN, University of MinnesotaSTEPHEN J. GUY, University of Minnesota

Individual-Oriented Model Crowd Evacuations Distributed Simulation

A. Gutierrez-Milla, F. Borges, R. Suppi, and E. Luque

Continuous Limit of a Crowd Motion and

Herding Model: Analysis and Numerical Simulations

By Martin Burger, Peter Markowich, Jan-Frederik Pietschmann

Modelling Crowd Scenes for Event Detection

Ernesto L. Andrade, Scott Blunsden and Robert B. Fisher

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