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Online Journal (JCSSM)

A Glossary for Research on Human Crowd Dynamics

Juliane Adrian, Nikolai Bode, Martyn Amos, Mitra Baratchi, Mira Beermann, Maik Boltes, Alessandro Corbetta, Guillaume Dezecache, John Drury , Zhijian Fu, Roland Geraerts, Steve Gwynne, Gesine Hofinger, Aoife Hunt, Tinus Kanters, Angelika Kneidl, Krisztina Konya, Gerta Köster, Mira Küpper, Georgios Michalareas, Fergus Neville, Evangelos Ntontis, Stephen Reicher, Enrico Ronchi, Andreas Schadschneider, Armin Seyfried, Alastair Shipman, Anna Sieben, Michael Spearpoint, Gavin Brent Sullivan, Anne Templeton, Federico Toschi, Zeynep Yücel, Francesco Zanlungo, Iker Zuriguel, Natalie van der Wal , Frank van Schadewijk, Cornelia von Krüchten, Nanda Wijermans

Abstract

This article presents a glossary of terms that are frequently used in research on human crowds. This topic is inherently multidisciplinary as it includes work in and across computer science, engineering, mathematics, physics, psychology and social science, for example. We do not view the glossary presented here as a collection of finalised and formal definitions. Instead, we suggest it is a snapshot of current views and the starting point of an ongoing process that we hope will be useful in providing some guidance on the use of terminology to develop a mutual understanding across disciplines. The glossary was developed collaboratively during a multidisciplinary meeting. We deliberately allow several definitions of terms, to reflect the confluence of disciplines in the field. This also reflects the fact not all contributors necessarily agree with all definitions in this glossary.

Crowd Dynamics

PILGRIM CROWD DYNAMICS – 

Abdulaziz Mousa Aljohani

Abstract

Among the steady progression of disasters worldwide lie the numerous instances of fatality where crowds gather. The scale of these is particularly high at the Hajj in Makkah, where there are exceptionally high numbers of pedestrians in a number of confined areas and, depending on the time of year, all in searing heat.

In order to reduce the likelihood of repetition in the future, the present thesis involved firstly determining the characteristics of the pedestrians attending the Hajj, and then collecting speed, flow and density data by observing them walking along one of the busiest roads between the Holy Mosque and the other holy sites, Ajyad Street. These were analyzed against various models from the literature including those of Greenshield, Weidmann and Greenberg, and it was found that none of these fitted convincingly, mostly because pilgrims do not walk at the maximum speeds that the crowd density allows. This thesis proposes the use instead of a maximum possible speed model based on a linear relationship between speed and density i.e……

Forecasting crowd dynamics through coarse-grained data analysis

Sebastien Motsch, Mehdi Moussa ̈ıd, Elsa G. Guillot, Mathieu Moreau, Julien Pettr ́e, Guy Theraulaz, C ́ecile Appert-Rolland, Pierre Degond

Abstract

Understanding and predicting the collective behaviour of crowds is essential to improve the efficiency of pedestrian flows in urban areas and minimize the risks of accidents at mass events. We advocate for the development of a “crowd forecasting system”, whereby real-time observations of crowds are coupled to fast and reliable models to produce rapid predictions of the crowd movement and eventually help crowd managers choose between tailored optimization strategies. Here, we propose a Bi-directional Macroscopic (BM) model as the core of such a system. Its key input is the fundamental diagram for bi-directional flows, i.e. the relation between the pedestrian fluxes and densities. We design and run a laboratory experiments involving a total of 119 participants walking in opposite directions in a circular corridor and show that the model is able to accurately capture the experimental data in a typical crowd forecasting situation. Finally, we propose a simple segregation strategy for enhancing the traffic efficiency, and use the BM model to determine the conditions under which this strategy would be beneficial. The BM model, therefore, could serve as a building block to develop on the fly prediction of crowd movements and help deploying real-time crowd optimization strategies.

Critical Situation Monitoring at Large Scale Events from Airborne Video Based Crowd Dynamics Analysis

Alexander Almer, Roland Perko, Helmut Schrom-Feiertag, Thomas Schnabel and Lucas Paletta

Abstract

Comprehensive monitoring of movement behaviour and raising dynamics in crowds allow an early detection and prediction of critical situations that may arise at large-scale events. This work presents a video based airborne moni- toring system enabling the automated analysis of crowd dynamics and to derive potentially critical situations. The results can be used to prevent critical situations by supporting security staff to control the crowd dynamics early enough. This approach enables preventing upraise of panic behaviour by automated early iden- tification of hazard zones and offering a reliable basis for early intervention by security forces. This approach allows the surveillance and analysis of large scale monitored areas of interest and raising specific alarms at the management and control system in case of potentially critical situations. The integrated modules extend classical mission management by providing essential decision support possibilities for assessing the situation and managing security and emergency crews on site within short time frames.

Crowd Dynamics and Control in High-Volume Metro Rail Stations

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

Abstract

Overcrowding in mass rapid transit stations is a chronic issue affecting daily commute in Metro Manila, Philippines. As a high-capacity public transportation, the Metro Rail Transit has been operating at a level above its intended capacity of 350,000 passengers daily. Despite numerous efforts in implementing an effective crowd control scheme, it still falls short in containing the formation of crowds and long lines, thus affecting the amount of time before they can proceed to the platforms. A crowd dynamics model of commuters in one of the high-volume terminal stations, the Taft Ave station, was developed to help discover emergent behavior in crowd formation and assess infrastructure preparedness. The agent-based model uses static floor fields derived from the MRT3 live feed, and implements a number of social force models to optimize the path-finding of the commuter agents. Internal face validation, historical validation and parameter variability-sensitivity analysis were employed to validate the crowd dynamics model and assess different operational scenarios. It was determined that during peak hours, when the expected crowd inflow may reach up to 7,500 commuters, at least 11 ticket booths and 6 turnstiles should be open to have low turnaround times of commuters. For non-peak hours, at least 10 ticket booths and 5 turnstiles are needed to handle a crowd inflow reaching up to 5,000 commuters. In the current set-up, the usual number of ticket booths open in the MRT Taft Station is 11, and there are usually 6 turnstiles open. It was observed that as the crowd inside the station increases to 200-250 commuters, there is a significant increase in the increase rate of the turnaround times of the commuters, which signifies the point at which the service provided starts to degrade and when officials should start to intervene.

Wei XIEa , Yu-chun ZHANG, Yan-ying CHENG, Shi-ming CHEN, Xuan-wen LIANG,

Abstract

Low visibility caused by smoke in fire can greatly affect movement speed and it should be taken into consideration in the fire performance-based design and evacuation calculation models. This paper aims to study evacuation performance of individuals and small groups under normal and visually handicapped condition. The evacuation experiment was conducted in a 5-layer office building with 75 subjects. Movement speed including horizontal speed and descending speed, and route choice of individuals and small groups were analysed and discussed in this paper. It can be concluded that horizontal speed was considerably higher than descending speed in good visibility condition and the speed differences among different participants were very great, but the gap between horizontal speed and descending speed narrowed significantly and the speed differences grew smaller with reduced visibility. The small group behaviour could make negative effect on movement speed when people evacuated under normal visibility condition but it could make positive impact in bad visibility condition since people’s fear of disorienting was relieved and message exchange rate was improved in a group. Both individuals and small groups generally tended to choose the most familiar route in normal visibility condition but ignored the shortest and unfamiliar route. People were more afraid to move vertically on stairs in low visibility compared to horizontal motion on flat surface such as corridor. It is suggested that proper evacuation guidance should be taken to improve the utilization of each exit in building in case of emergency.

Statistical analysis of the crowd dynamics in Al-Masjid Al-Nabawi in the city of Medina, Saudi Arabia

Hassan M. Al-Ahmadi , Wael S. Alhalabi , Rezqallah Hasan Malkawi , Imran Reza 
Abstract
Not included in this link

Early Warning of Human Crowds Based on Query Data from Baidu Map: Analysis Based on Shanghai Stampede

Jingbo Zhou, Hongbin Pei and Haishan Wu

ABSTRACT

Without sufficient preparation and on-site management, the mass scale unexpected huge human crowd is a serious threat to public safety. A recent impressive tragedy is the 2014 Shanghai Stampede, where 36 people were killed and 49 were injured in celebration of the New Year’s Eve on Decem- ber 31th 2014 in the Shanghai Bund. Due to the innately stochastic and complicated individual movement, it is not easy to predict collective gatherings, which potentially leads to crowd events. In this paper, with leveraging the big data generated on Baidu map, we propose a novel approach to early warning such potential crowd disasters, which has pro- found public benefits. An insightful observation is that, with the prevalence and convenience of mobile map service, users usually search on the Baidu map to plan a routine. There- fore, aggregating users’ query data on Baidu map can obtain priori and indication information for estimating future hu- man population in a specific area ahead of time. Our careful analysis and deep investigation on the Baidu map data on various events also demonstrates a strong correlation pat- tern between the number of map query and the number of positioning users in an area. Based on such observation, we propose a decision method utilizing query data on Baidu map to invoke warnings for potential crowd events about 1 ∼ 3 hours in advance. Then we also construct a machine learning model with heterogeneous data (such as query data and mobile positioning data) to quantitatively measure the risk of the potential crowd disasters. We evaluate the effect- iveness of our methods on the data of Baidu map

Whistland: An Augmented Reality Crowd-Mapping System for Civil Protection and Emergency Management
Gioele Luchetti, Adriano Mancini, Mirco Sturari , Emanuele Frontoni and Primo Zingaretti

Abstract

The prevention and correct management of natural disaster event sequences play a key role in saving human lives. The availability of embedded and mobile smart computing systems opens new roads for the management of land and infrastructures by civil protection operators. To date, research has explored the use of social networks for the management of disasters connected to meteorological/hydrogeological events or earthquakes, but without emphasis on the importance of an integrated system. The main feature of the Whistland system proposed in this paper is to make synergistic use of augmented reality (AR), crowd-mapping (CM), social networks, the Internet of Things (IoT) and wireless sensor networks (WSN) by exploiting technologies and frameworks of Web 2.0 and GIS 2.0 to make informed decisions about the chain of events. The Whistland system is composed of a geo-server, a mobile application with AR and an analytics dashboard. The geo-server acts as the hub of the sensor and social networks. The abstracted concept in this sense is the transformation of the user domain into “intelligent sensors” for the whole scope of crisis management. The social network integration is made through an efficient pointer-like mechanism that keeps the storage requirement low through a mobile application based on an augmented reality engine and provides qualitative information that sensors are unable to capture. Real-time analyses, geo-searches and the capability to examine event histories with an augmented reality engine all help the stakeholders to understand better the state of the resources under observation/monitoring. The system has been extensively tested in the programmed maintenance of river basins, where it is necessary to log maintenance activities in order to keep the riverbank clean: a significant use-case in many countries affected by hydro-geological instability.

Yeen Lai Khong, Bee Chen Ooi, Kok Eng Tan , Salizatul Aizah Binti Ibrahim, and Peck Ling Tee

Abstract.

Waiting in line is a common experience in daily life, whether for a table at a popular restaurant or for the service at a bank. This experience is not always pleasant for most of people because they always have to wait for a long time to be serviced. The ability to interact with waiting customers is highly desirable because it allows businesses the opportunity to optimize their existing services and offer new services to waiting customers. However, interacting with individuals waiting in a queue has been inefficient and costly because employees must either talk with each waiting customer on an ongoing basis or the business must provide high tech devices that interact with each waiting customer. Agile methodology which will be used to develop this application, it incorporates the SDLC phases starting from the Planning phase up to the Maintenance phase. End of the research, we found that majority of respondents are prefer to use the proposed system compared with current method.

Efficient numerical methods for multiscale crowd dynamics with emotional contagion

Li Wang, Martin B. Short, Andrea L. Bertozzi

Abstract

In this paper, we develop two efficient numerical methods for a multiscale kinetic equa- tion in the context of crowd dynamics with emotional contagion [A. Bertozzi, J. Rosado, M. Short and L. Wang, Contagion shocks in one dimension, J. Stat. Phys. 158 (2014) 647–664]. In the continuum limit, the mesoscopic kinetic equation produces a natural Eulerian limit with nonlocal interactions. However, such limit ceases to be valid when the underlying microscopic particle characteristics cross, corresponding to the blow up of the solution in the Eulerian system. One method is to couple these two situations — using Eulerian dynamics for regions without characteristic crossing and kinetic evolution for regions with characteristic crossing. For such a hybrid setting, we provide a regime indicator based on the macroscopic density and fear level, and propose an interface condition via continuity to connect these two regimes. The other method is based on a level set formulation for the continuum system. The level set equation shares similar forms as the kinetic equation, and it successfully captures the multi-valued solution in velocity, which implies that the multi-valued solution other than the viscosity solution should be the physically relevant ones for the continuum system. Numerical examples are presented to show the efficiency of these new methods.

Fire department perspective: crowd dynamics and safety at outside events

Griggs, Rick

Abstract

Fire departments often respond to incidents at crowded events with no prior planning or coordination with other agencies. The result can be decreased safety for patrons at the events. The purpose of this thesis is to understand causes of injuries at crowded, outside venues and what could make these events safer. This thesis asks how fire department personnel can plan for the safety and care of large crowds at outside venues. The research design includes a review of literature on crowd dynamics and example incidents. Using root cause analysis, this thesis analyzes four case studies: 1989 Hillsborough soccer match, 2011 Reno Air Race, the 2013 Boston Marathon bombing, and 2014 Travis Air Force Base Air Show. The success of the Reno Air Race and Boston Marathon rescue personnel in taking care of injured victims can be attributed to careful planning by stakeholders before the events took place. This thesis recommends that before large, crowded events, stakeholders establish relationships and that all stakeholders participate in careful planning and realistic training. This planning and training should include interoperability of communications, roles for volunteer staff, and ways to prevent and decrease overcrowding. Finally, this thesis recommends strategies to educate event patrons on safety.

An empirical study of crowd and pedestrian dynamics  the impact of different angle paths and grouping

Andrea Gorrini, Stefania Bandini, Majid Sarvi, Charitha Dias, Nirajan Shiwakoti

Abstract
An analytical study is proposed in this paper to investigate pedestrian crowd dynamics from a multi-disciplinary approach (i.e. traffic engineering and social science)  focusing on the impact of environment physical features and social interaction on pedestrian movement dynamics in high-density situations on pedestrian movement dynamics in high-density situations. Taking advantage of previous studies that highlighted the importance of turning movements of crowd during evacuations, we empirically investigated the impact of angled paths on orderly crowd egress flows. We also proposed to consider the social interaction among pedestrians, taking into account the presence of groups and their proxemics behavior while walking. Results of the flow rates level and walking speed of different scenarios studied in this work are presented (0°, 45°, 60° and 90° angle degrees). These showedthat in high-density situations the walking speed of group members waslower compared to the singles within all scenarios studied, because of the need to stay close to own group members while walking. Likewise, the angle path with 60° degrees (compared to the scenario of corridor with 0° degrees) has a significant negative impact on both the flow rate and walking speed. These
results could be of notable interest for allgeneric crowd models aiming at replicating crowd
dynamics.

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

Abstract

Perceiving crowd emotions and understand the sit- uation is vital to control the situations in surveillance appli- cations. This paper introduces the evolution of methods for crowd emotion perception based on bio-inspired probabilistic models. The emotions have been perceived both in an offline and online manner from the crowd. We focus on the perception of emotion from crowd behavior and dynamics. The paper explains few probabilistic algorithms and compares these for detection of emotion of crowds and proposes a probabilistic modelling approach which is trained on data to perceive the emotions of the crowd in an area under surveillance. Emotions are defined as evolving dynamic patterns arising due to interaction of people in an environment with their relationships to the past interaction patterns. Camera sensors are used to track the motion of the individuals within a crowd scenario under observation. The data mining techniques are used to distinguish between different behaviors and events into positive and negative emotions. The results have been evaluated using simulated data from a proposed office environment.

A comparative study of pedestrian crowd flow at middle and corner exits

Nirajan Shiwakoti, Xiaomeng Shi, Zhirui Ye, Yiwen Liu, Junkai Lin

Abstract

Bottleneck formed due to complex architectural configurations can create hazardous situations for pedestrian crowd as have been noted from the previous documented studies of crowd disasters. Existing studies demonstrate that escape layout and adjustment of architectural features in an escape area can have an effect on the outflow and safety of the pedestrian crowd. However, all the observed results are either the mathematical prediction or empirical experiments with non-human organisms. There is lack of empirical data on human crowds that explores the effect of architectural configurations on the outflow of the people. This is critical for verification of the model intended to simulate the pedestrian crowd behaviour in built environment such as train stations, stadiums and shopping malls.

In this paper, the comparative performance of location of two exits (middle vs. corner exit) is explored with 50 human participants in a controlled laboratory egress experiments under normal walking and slow running (faster walking) conditions. Each set of experiment was repeated for three times and a total of 12 experimental trials were conducted. It was observed that compared to middle exit, corner exit was efficient in terms of outflow by around 8.7% under normal walking condition and around 4.2% under slow running or faster walking condition. Further, it was observed that with corner exit, there were less long headways (successive time gap between two pedestrians) and potential conflicts as compared to middle exit. The findings from this paper have demonstrated that there is a scope to adjust the architectural elements to optimize the maximum outflow and enhance the pedestrian crowd safety at the egress point. Further the output from the experiments can be used to develop and verify mathematical models intended to simulate pedestrian crowd evacuation.

Analysis of Stampede Emergency Management Capability in Subway Station Based on Analytic Hierarchy Process

Yingying Guo

Abstract

Large crowds cause stampede and casualties with constant development and widely use of the subway, which has been one of the major factors in negative social impact. And thus pose a major challenge to the emergency management. This study intends to improve the ability to respond to emergencies is of practical significance. The current explorative study aims to use Analytic Hierarchy Process (AHP) to have a comprehensive evaluation of stampede emergency management capability in subway station. An indicator system is constructed, including four main criteria such as prevention and preparation, monitoring and early-warning, emergency response and rescue, restoration and reconstruction and 19 sub-factors. The results of the AHP analyses indicate that emergency response and rescue phase and some other sub-factors are the most important criteria which occupy a heavy weight. In addition, recommendations for improving the capability of stampede emergence management are also included in the report as well as suggestions for follow-on analyses.

Framework to mitigate risks of crowd disasters at mass events in public urban space

Sjouke Wieringa, MSc., Prof. dr. Serge Hoogendoorn, Prof.dr. Pieter van Gelder

Abstract

More and more people visit mass events, while also the number of mass events is increasing. Mass events in urban space have only limited infrastructure available, and are thus more subject to risk of crowd disaster. This paper proposes a crowd management framework for mitigating risks of crowd disasters at mass events in the public urban space. The framework consists of six steps, with the final aim to quantify the consequences of measures near bottlenecks. The most important elements of the framework are the layered crowd disaster model (showing how the traffic situation might develop into a crowd disaster), and the scenario measure charts (showing which preventive measures may be applied in which situation). The risk of crowd disasters is calculated as the product of the level-of-service and the duration of this level-of-service. The advice provided in this evaluation tool incorporates stakeholders’ tolerance towards risks, using a multi criteria analysis in which the weights for the various assessment criteria can be adapted to the situation at hand. The output of the framework is suitable for tactical decision-making upon risk mitigation strategies for mass events in the public urban space.

An Anticipative Crowd Management System Preventing Clogging in Exits During Pedestrian Evacuation Processes

Ioakeim G. Georgoudas, Georgios Ch. Sirakoulis, Member, IEEE, and Ioannis Th. Andreadis

Abstract

This paper presents an anticipative system which operates during pedestrian evacuation processes and prevents escape points from congestion. The processing framework of the system includes four discrete stages: a) the detection and tracking of pedestrians, b) the estimation of possible route for the very near future, indicating possible congestion in exits, c) the proposal of free and nearby escape alternatives, and d) the activation of guiding signals, sound and optical. Detection and tracking of pedestrians is based on an enhanced implementation of a system proposed by Viola, Jones, and Snow that incorporates both appearance and motion information in near real-time. At any moment, detected pedestrians can instantly be defined as the initial condition of the second stage of the system, i.e., the route estimation model. Route estimation is enabled by a dynamic model inspired by electrostatic-induced potential fields. The model combines electrostatic-induced potential fields to incorporate flexibility in the movement of pedestrians. It is based on Cellular Automata (CA), thus taking advantage of their inherent ability to represent effectively phenomena of arbitrary complexity. Presumable congestion during crowd egress, leads to the prompt activation of sound and optical signals that guide pedestrians towards alternative escaping points. Anticipative crowd management has not been thoroughly employed and this system aims at constituting an effective proposal.

Utilising gamification approaches to derive crowd pattern/crowd context from aerial images of major events

Gebru Welay Gerezigiher

Abstract

A large number of casualties occur during emergencies in highly-crowded public spaces of major events like annual anniversaries, religious festivals, big parties and football matches due to stampedes. It has been often observed that poor resource management is one of the key areas that could be improved to solve this problem. In this study,a geo-game-based approach has been adopted to alert responsible authorities of highly crowded regions as an early warning system and also provide them with optimal dispersal routes. In the Android-based game that was developed for this study, the players could draw polygons on real-time imageries of the area under study obtained from unmanned aerial vehicles and classify them into categories based on how crowded the region is. This data is submitted to a web server which is processed to find suitable least-cost routes by which the people in the crowded regions can be brought to safety in case of an emergency. The spatial distribution of people could be forwarded to appropriate authorities in-charge of the administration highlighting extremely crowded regions which need their attention thereby prompting redirection of security personnel. Additionally, the calculated dispersal routes could be used by them as suggestions to avoid a stampede and ensure safety in case the situation turns worse.

Turbulence and Shock-Waves in Crowd Dynamics

Vladimir G. Ivancevic and Darryn J. Reid

Abstract

In this paper we analyze crowd turbulence from both classical and quantum perspective. We analyze various crowd waves and collisions using crowd macroscopic wave function. In particular, we will show that nonlinear Schr ̈odinger (NLS) equation is fundamental for quan- tum turbulence, while its closed-form solutions include shock-waves, solitons and rogue waves, as well as planar de Broglie’s waves. We start by modeling various crowd flows using classical fluid dynamics, based on Navier–Stokes equations. Then, we model turbulent crowd flows using quantum turbulence in Bose-Einstein condensation, based on modified NLS equation.

Understanding pedestrian crowd merging behavior

Kayvan Aghabayk , Omid Ejtemai , Majid Sarvi , Amir Sobhani

Abstract

Different behaviors of pedestrian under complex situations such as turning and crossing have been investigated in the past. However, few studies considered the behaviors of pedestrians in merging areas despite the fact that this situation is very common in built environment such as exit points of railway stations and stadium. Notwithstanding of the importance of this phenomenon in pedestrian movements in particular due to creating bottleneck areas, the existing research on merging area is limited to T-junctions or staircases. This study investigates the merging behaviors of pedestrians under different scenarios such as various angles and pedestrian speed. The outcome of this research provides an insight into the understanding of crowd behaviors in merging areas.

A Large Scale Crowd Density Classification using Spatio-Temporal Local Binary Pattern

Sonu Lamba, Neeta Nain

Abstract

Increasing world wide population is leading to dense crowd gathering at public places. Due to mass gathering at large scale, crowd related disaster has been frequently occurred. In order to prevent crowd calamities, automated crowd scene analysis has been a topic of great interest. Density is the status of crowd which is essential to classify in visual surveillance system primarily for security aspects. Most of the existing techniques work on detection and tracking of individuals. Due
to fewer pixels per target, multiple occlusion and perspective effects etc., detection and tracking of individuals is a complex task in dense crowd scenarios. This paper presents a novel strategy for large scale crowd density classification powered by dynamic texture analysis. This approach consists of an interest points detection followed by spatio-temporal feature extraction. A rotation invariant spatio-temporal local binary (RIST-LBP) pattern is proposed to extract dynamic texture of the moving
crowd. Further, a multi-class support vector regression is adopted for density classification. We also include a tracking step which tracks the selected interest points over the video frames for crow
flow estimation. We validate our proposed approach on three different datasets such as PETS, UCF and CUHK which vary in density ranging from low to very dense. The performance of our proposed approach is compared with most commonly used pixel based statistics. Our approach has the advantage of low computational complexity with high efficiency in real world applications of video surveillance.

A Discrete Spheropolygon Model for Calculation of Stress in Crowd Dynamics

Fernando Alonso-Marroqu ́ın, Jonathan Busch, Alvaro Ram ́ırez and Celia Lozano

Abstract

Several models have been presented to evaluate flow rates in pedestrian dynamics, yet very few focus on the calculation of the stress experienced by pedestrians under high density. With this aim, a pedestrian dynamics model is implemented to calculate the stress developed under crowd conditions. The model is based on an extension of a granular dynamics model to account contact forces, ground reaction forces and torques in the pedestrians. Contact stiffness is obtained from biomedical journal articles, and coefficient of restitution is obtained by direct observations of energy loss in collisions. Existing rotational equations of motion are modified to incorporate a rotational viscous component, which allows pedestrians to come to a comfortable stop after a collision rather than rotating indefinitely. The shape of the pedestrian is obtained from a bird’s eye, cross sectional view of the human chest cavity and arms, which was edited to produce an enclosed shape. This shape is them approximated by a spheropolygon, which is a mathematical object that allows real-time simulation of complex-shape particles. The proposed method provides real benefits to the accuracy on particle shape representation, and rotational dynamics of pedestrians at micro-simulation level. It provides a new tool to calculate the risk of injuries and asphyxiation when people are trapped in dense crowds that lead to development of high pressure.

Crowd Dynamics

G. Keith Still
PhD Thesis
University of Warwick

Abstract

Crowd dynamics are complex. This thesis examines the nature of the crowd and its dynamics with specific reference to the issues of crowd safety. A model (Legion) was developed that simulates the crowd as an emergent phenomenon using simulated annealing and mobile cellular automata. We outline the elements of that model based on the interaction of four parameters: Objective, Motility, Constraint and Assimilation. The model treats every entity as an individual and it can simulate how people read and react to their environment in a variety of conditions, this allows the user to study a wide range of crowd dynamics in different geometries and highlights the interactions of the crowd with its environment. We demonstrate that the model runs in polynomial time and can be used to assess the limits of crowd safety during normal and emergency egress.

Over the last 10 years there have been many incidents of crowd related disasters. We outline deficiencies in the existing guidelines relating to crowds and, by comparison and contrast with the model, we highlight specific areas where the guides may be improved. We demonstrate that the model is capable of reproducing crowd dynamics without additional parameters thus satisfying Occam s Razor.

We propose an alternative approach to assessing the dynamics of the crowd through the use of the simulation and analysis of least effort behaviour. The model is tested against known crowd dynamics from field studies, including Wembley Stadium, Balham Station and the Hong Kong Jockey club. Finally we test the model in a variety of applications where crowd related incidents warrant structural alterations at client sites. We demonstrate that the model explains the variance in a variety of field measurements, that it is robust and that it can be applied to future designs where safety and crowd comfort are criteria for design and cost savings.

Pedestrian, Crowd and Evacuation Dynamics

DIRK HELBING ANDERS JOHANSSON

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

Introduction

The emergence of new, functional or complex collective behaviors in social systems has fascinated many scientists. One of the primary questions in this field is how cooper- ation or coordination patterns originate based on elemen- tary individual interactions. While one could think that these are a result of intelligent human actions, it turns out that much simpler models assuming automatic responses can reproduce the observations very well. This suggests that humans are using their intelligence primarily for more complicated tasks, but also that simple interactions can lead to intelligent patterns of motion. Of course, it is rea- sonable to assume that these interactions are the result of a previous learning process that has optimized the auto- matic response in terms of minimizing collisions and de- lays. This, however, seems to be sufficient to explain most observations.

In this contribution, we will start with a short his- tory of pedestrian modeling and, then, introduce a sim- plified model of pedestrian interactions, the “social force model”. Furthermore, we will discuss its calibration us- ing video tracking data. Next, we will turn to the subject of crowd dynamics, as one typically finds the formation of large-scale spatio-temporal patterns of motion, when many pedestrians interact with each other. These patterns will be discussed in some detail before we will turn to evac- uation situations and cases of extreme densities, where one can sometimes observe the breakdown of coordina- tion. Finally, we will address possibilities to design im- proved pedestrian facilities, using special evolutionary al- gorithms.

The Dynamics of Crowds

Gareth William Parry

MSc. in Modern Applications of Mathematics

University of Bath

Abstract

Crowds pose an interesting example of a complex system in which emergent behaviour is observed out of the interaction of many individual agents. This behaviour can be very important in the safe design of sports and other stadia, especially in the case of possible emergency situations. For this reason crowd dynamics is of great interest to architects. The purpose of this project is to review the current literature on crowd dynamics and to look at some simulations of different types of crowd behaviour in certain specific situations namely: the meeting of two crowds in a ’scramble crossing’, the motion of a crowd though an exit and the response of a crowd to an emergency (such as a fire). The student will implement a differential equation model of the crowd crossing problem. In particular, they will study the emergent behaviour that arises in the scramble crossing problem and see how this depends on various parameters relating to the individual actions of the members of the crowd.

A Proposed Computer-Based System Architecture for Crowd Management of Pilgrims using Thermography

Mohamed O. Khozium; Adnan G. Abuarafah; and Essam AbdRabou

Abstract:

Over the years, overcrowding and difficulties in crowd control have resulted in a number of fatal accidents during the Hajj. Despite many efforts and improvements for roads and footbridges, ensuring the safety of pilgrims continues to challenge especially with the annual increase of the number of pilgrims. The challenge has attracted many researchers who provided several methodologies for crowd monitoring and estimation of its density. This paper proposes to extend an earlier monitoring effort done by the same authors to develop a decision support system allows for close monitoring and control of crowd movements. It incorporates data acquisition and processing via several thermal cameras deployed as sensors at strategic points on Nafra (Arafat to Muzdalifah) access roads. The sensors are linked to an analysis module, which in turn measures crowd flow and density in real time. When crowds become too dense, an alarm is triggered according to different density levels. At this point, the integrated decision support system generates different alternatives to the controllers in order for them to take the appropriate actions. The paper illustrates the proposed system component. It also describes the architecture of each component as well as the architecture of the entire system. The system can contribute to provide complete safety for crowds during the Hajj event that attracts millions each year.

Perceived Crowd Safety in Large Space Buildings: The Confirmatory Factor Analysis of Perceived Risk Variables

Mohammed Alkhadim , Kassim Gidado, and Noel Painting

Abstract:

In crowded large space buildings, safety is one of the most important concerns for facilities managers. Within the built environment, safety has been classified into two main parts: objective safety (normative and substantive) and subjective safety (perceived). A lot of emphasis has been given to objective safety, but research has shown that subjective safety could be equally important and cannot be overlooked. A flow of risk factors within crowded large space buildings such as sports stadiums, concert halls, and religious buildings have resulted in crowd disasters in various venues across the world. Every user in such facilities during mass gathering can be exposed to safety risks, which can be mitigated by using effective risk management as a component of facilities management. This paper focused on subjective safety and aimed to validate the measurement model of latent constructs measuring 12 risk constructs of perceived safety in crowded large space buildings. Two theoretical frameworks (FIST and Six dimensions and loci of crowd disaster) and other relevant literature were used to generate items for the respective constructs. The research chose to use the Holy Mosque in Makkah as a case study (crowded large space building), which is 356,800 square metres with a maximum capacity of two million users (pilgrims). Data was collected using iPad devices via a group-administered questionnaire distributed to 1,940 pilgrims across 62 different nationalities. The data wasanalysed using the Statistical Packages for the Social Sciences (SPSS) and Analysis of Moment Structure (AMOS) for descriptive analysis and Confirmatory Factor Analysis (CFA) respectively. CFA has validated the measurement model of the 12 constructs for unidimensionality, validity, and reliability.

Crowd Modelling

Simulation of people’s movements on floors using social force model

Mohammed, A; Pavic, A

ABSTRACT

Vibration serviceability assessment of floors has been traditionally based on a scenario of a single person walking along a path which will generate maximum vibration level. This is due to the difficulty of predicting the real positions and paths of the walking people. With such a design scenario, it is possible to obtain calculated responses, which could be both over- or under- estimated, depending on the specifics. This could be due to considering only one person walking along one walking path in the simulations. This aspect in the design guidelines could be improved if realistic modelling of people’s movements is utilised. Hence, this paper examines the performance of the social force model to simulate the behaviour of people’s movements on floors. This method has been widely used to model a crowd of people in evacuation and panic situations. However, it has been reported in the literature that this approach could be used to model people’s movements in normal situations as well. The simulation carried out in this paper focuses on the interaction between walking people themselves and between walking people and the surrounding boundaries in typical office floors. The results show that reasonable and realistic behaviour of the floor occupants could be obtained using the social force model. Furthermore, utilising the ‘heatmap’ can help the designers to visualise and obtain information about the proportion of time spent by walking individuals at various points on the floor. This approach can be adopted in a more realistic procedure for the vibration serviceability assessment of floors.

Exploring Determinants of Pre-movement Delays in a Virtual Crowd Evacuation Experiment

Nikolai W. F. Bode, Edward A. Codling

Abstract

Understanding evacuations of high-occupancy buildings presents a major challenge in fire safety science. The total time individuals require to exit a building includes the time it takes them to respond to an alarm and decide to evacuate (pre-movement) and the time it takes them to walk along their chosen exit route (movement). Previous work has shown that variation in pre-movement times is responsible for substantial evacuation delays, but few controlled experiments on this have been conducted. Here, we present a virtual experiment that investigates the level of risk individuals take by collecting virtual objects before evacuating. We determine how over 1200 participants, who were recruited from visitors to the London Science Museum, respond to three factors: a reduction in their knowledge of a building, a change in the behaviour of other simulated evacuees and a change in how they are attached to the objects they can collect (potential gain versus loss). We confirm that collecting more objects is risky, as it affects evacuation success. In our experiment, 44.6% of participants choose extreme strategies by collecting either all or none of the available objects before evacuating. While the adoption of extreme strategies is affected by all three factors we investigate, the only factor that significantly increases the average number of objects participants collect, regardless of extreme strategies, is loss aversion. Our work shows the potential of virtual experiments to safely, quickly and cheaply scope processes causing pre-movement time delays in crowd evacuations. This provides a starting point for further research.

Abstract

In a pioneering work in Nature journal, a counterintuitive prediction that escape rates of people under panic conditions will be enhanced if an obstacle such as a column or a barrier is placed on the upstream side of an exit was demonstrated through a simulation model. However, the prediction lacked empirical verification. Despite the substantial works in this topic in the past decade, there is currently a lack of knowledge on how and to what extent the obstacle near an exit can enhance the pedestrian outflow at the bottlenecks during emergency escape.

Therefore, the aim of this paper is to present a critical review on the performance of an obstacle near an exit and identify future research directions. It is found that although there is a general consensus on the beneficial effect of an obstacle, there is a large uncertainty on the situations on which the positive effect of obstacle could be observed. In addition, verification of the models prediction with empirical data with humans is still largely unexplored. There is no clear established relationship between the exit width, obstacle distance and obstacle size/shape. Also, quantitative understanding of the nature of the clogging transition due to obstacle is a challenging task. Further, researchers have questioned the implementation of such obstacles at bottlenecks in real life scenario. A systematic approach of optimising architectural adjustments that enhances escape dynamics of pedestrians crowd within an escape area or a building or other public infrastructures needs to be conducted in future.

Crowd density estimation in still images using multiple local features and boosting regression ensemble

Muhammad Shahid Saleem, Muhammad Jaleed Khan, Khurram Khurshid, Muhammad Shehzad Hanif

Abstract

Crowd density estimation is a challenging research problem in computer vision and has many applications in commercial and defense sectors. Various crowd density estimation methods have been proposed by researchers in the past, but there is an utmost need for accurate, robust and efficient crowd density estimation techniques for its practical implementation. In this paper, we propose a fine-tuned and computationally economical, ensemble regression-based machine learning model for crowd density estimation. The WorldExpo’10 dataset has been used for experimental analysis and model performance evaluation. We extract variety of features in texture-based features such as gray-level co-occurrence matrix, local binary pattern and histogram of oriented gradients, structure-based features such as perimeter pixel and the orientation of pixels, and segment-based handcrafted features from each patch of the image and use an optimum combination of these features as input to the regression model. To achieve optimized memory utilization and faster speed, principal component analysis is employed to reduce the dimensions of the lengthy feature vector. Extensive experiments on different fronts ranging from the model hyperparameter optimization, features optimization and features selection were conducted, and at each step, we selected the most favorable results as input to the optimized model. The performance of the model is evaluated based on two popular metrics, i.e., mean absolute error and mean squared error. The comparative analysis shows that the proposed system outperforms the former methods tested on the WorldExpo’10 dataset.

Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck

Xiaomeng Shi , Zhirui Ye, Nirajan Shiwakoti, Dounan Tang, Junkai Lin,

Abstract:

Recent advances in bottleneck studies have highlighted that different architectural adjustments at the exit may reduce the probability of clogging at the exit thereby enhancing the outflow of the individuals. However, those studies are mostly limited to the controlled experiments with non–human organisms or predictions from simulation models. Complementary data with human subjects to test the model’s prediction is limited in literature. This study aims to examine the effect of different geometrical layouts at the exit towards the pedestrian flow via controlled laboratory experiments with human participants. The experimental setups involve pedestrian flow through 14 different geometrical configurations that include different exit locations and obstacles near exit under normal and slow running conditions. It was found that corner exit performed better than middle exit under same obstacle condition. Further, it was observed that the effectiveness of obstacle is sensitive to its size and distance from the exit. Thus, with careful architectural adjustment within a standard escape area, a substantial increase in outflow under normal and slow running conditions could be achieved. However, it was also observed that placing the obstacle too close to the exit can reduce outflow under both normal and slow running conditions. Moreover, we could not observe “faster–is–slower” effect under slow running condition and instead noticed “faster–is–faster” effect. In addition, the power law fitted headway distribution demonstrated that any architectural configurations that enhanced the outflow have higher exponent value compared to the other configuration that negates the outflow. The findings from this paper demonstrate that there is a scope to adjust the architectural elements to optimize the maximum outflow at the egress point. Further, the output from the experiments can be used to develop and verify mathematical models intended to simulate crowd evacuation.

Virtual reality crowd simulation: effects of agent density on user experience and behaviour

Patrick Dickinson, Kathrin Gerling, Kieran Hicks, John Murray, John Shearer

Abstract

Agent-based crowd simulations are used for modelling building and space usage, allowing designers to explore hypothetical real-world scenarios, including extraordinary events such as evacuations. Existing work which engages virtual reality (VR) as a platform for crowd simulations has been primarily focussed on the validation of simulation models through observation; the use of interactions such as gaze to enhance a sense of immersion; or studies of proxemics. In this work, we extend previous studies of proxemics and examine the effects of varying crowd density on user experience and behaviour. We have created a simulation in which participants walk freely and perform a routine manual task, whilst interacting with agents controlled by a typical social force simulation model. We examine and report the effects of crowd density on both affective state and behaviour. Our results show a significant increase in negative affect with density, measured using a self-report scale. We further show significant differences in some aspects of user behaviours, using video analysis, and discuss how our results relate to VR simulation design for mixed human–agent scenarios.

3D visual simulation of individual and crowd behavior in earthquake evacuation

Tingting Liu, Zhen Liu, Minhua Ma, Tian Chen, Cuijuan Liu and Yanjie Chai

Abstract

Simulation of behaviors in emergencies is an interesting subject that helps to understand evacuation processes and to give out warnings for contingency plans. Individual and crowd behaviors in the earthquake are different from those under normal circumstances. Panic will spread in the crowd and cause chaos. Without considering emotion, most existing behavioral simulation methods analyze the movement of people from the point of view of mechanics. After summarizing existing studies, a new simulation method is discussed in this paper. First, 3D virtual scenes are constructed with the proposed platform. Second, an individual cognitive architecture, which integrates perception, motivation, behavior, emo- tion, and personality, is proposed. Typical behaviors are analyzed and individual evacuation animations are realized with data captured by motion capture devices. Quantitative descriptions are presented to describe emotional changes in indi- vidual evacuation. Facial expression animation is used to represent individuals’ emotions. Finally, a crowd behavior model is designed on the basis of a social force model. Experiments are carried out to validate the proposed method. Results showed that individuals’ behavior, emotional changes, and crowd aggregation can be well simulated. Users can learn eva- cuation processes from many angles. The method can be an intuitional approach to safety education and crowd management.

Crowd of Virtual Humans : a New Approach for Real Time Navigation in Complex and Structured Environments
Fabrice Lamarche, Stéphane Donikian

Abstract

The navigation activity is an every day practice for any human being capable of locomotion. Our objective in this work is to reproduce this crucial human activity inside virtual environments. Putting together the high complexity of a realistic environment such as a city, a big amount of virtual humans and the real-time con- straint requires to optimize each aspect of the animation process. In this paper, we present a suitable topological structuring of the geometric environment to allow fast path finding as well as an efficient reactive navigation algorithm for virtual humans evolving inside a crowd.

Macroscopic effects of microscopic forces between agents in crowd models

Colin M. Henein and Tony White

ABSTRACT

Crowd scenarios have attracted attention from computer modellers, perhaps because of the impracticality of studying the phenomenon by traditional experimental methods. For example, Kirchner has proposed an agent-based crowd model inspired by fields of elementary particles [2], but chose not to incorporate crowd forces. We argue that crowd forces (and associated injuries) are an essential characteristic of crowds, and that their omission will negatively affect the model’s ability to make predictions (e.g. time for a crowd to pass through an exit). To support this position we describe an evolution of Kirchner’s model that includes a vector-based particle field to represent forces. We show qualitative and quantitative differences compared to Kirchner’s model when force is included. The Swarm Force model demonstrates – by showing non-linear effects of force – the necessity of force in crowd models.

Realistic following behaviors for crowd simulation

S. Lemercier. Jelic R. Kulpa J. Hua J. Fehrenbach P. Degond. Appert-Rolland S. Donikian J. Pettré

Abstract

While walking through a crowd, a pedestrian experiences a large number of interactions with his neighbors. The nature of these interactions is varied, and it has been observed that macroscopic phenomena emerge from the combination of these local interactions. Crowd models have hitherto considered collision avoidance as the unique type of interactions between individuals, few have considered walking in groups. By contrast, our paper focuses on interactions due to the following behaviors of pedestrians. Following is frequently observed when people walk in corridors or when they queue. Typical macroscopic stop-and-go waves emerge under such traffic conditions. Our contributions are, first, an experimental study on following behaviors, second, a numerical model for simulating such interactions, and third, its calibration, evaluation and applications. Through an experimental approach, we elaborate and calibrate a model from microscopic analysis of real kinematics data collected during experiments. We carefully evaluate our model both at the microscopic and the macroscopic levels. We also demonstrate our approach on applications where following interactions are prominent.

Modelling contra-flow in crowd dynamics DEM simulation
Alastair Smith , Christopher James , Richard Jones , Paul Langston, Edward Lester , John Drury

abstract

This paper highlights the growing need for a realistic crowd simulation in the design of large venues such as concert halls and stadia. A discrete element method (DEM) technique for modelling crowd dynamics has been developed that represents each person within the model as 3 overlapping circles, a position, ori- entation and velocity in 2D. Contact forces between elements are included in the model as well as psy- chological forces, motive forces and moments. The motion of each person is then modelled in a Newtonian manner with a numerical integration time-stepping scheme. The model has been shown pre- viously to work well in predicting egress. In this paper the predicted model behaviour is compared to actual video footage shot at various locations around University Park Campus, Nottingham. It did not match well to the video footage when people are moving towards each other, as in cases of contra-flow on a walkway. In order to improve the model, a general algorithm for ‘avoidance’ was included which appeared to make the model significantly more realistic in these cases. The paper also shows areas for further potential development, such as incorporating people into associative groups such as family or friends.

Branislav Ulicny and Daniel Thalmann

Abstract

While virtual crowds are becoming common in non-real-time applications, the real-time domain is still relatively unexplored. In this paper we discuss the challenges involved in creating such simulations, especially the need to efficiently manage variety. We introduce the concept of levels of variety. Then we present our work on crowd behaviour simulation aimed at interactive real-time applications such as computer games or virtual environments. We define a modular behavioural architecture of a multi-agent system allowing autonomous and scripted behaviour of agents supporting variety. Finally we show applications of our system in a virtual reality training system and a virtual heritage reconstruction.

Crowd and environmental management during mass gatherings

DrAndersJohanssonPhD, ProfMichaelBattyPhD, KonradHayashiMD, OsamaAl BarPhD, DavidMarcozziMD, ProfZiad AMemishMD

Summary

Crowds are a feature of large cities, occurring not only at mass gatherings but also at routine events such as the journey to work. To address extreme crowding, various computer models for crowd movement have been developed in the past decade, and we review these and show how they can be used to identify health and safety issues. State-of-the-art models that simulate the spread of epidemics operate on a population level, but the collection of fine-scale data might enable the development of models for epidemics that operate on a microscopic scale, similar to models for crowd movement. We provide an example of such simulations, showing how an individual-based crowd model can mirror aggregate susceptible–infected–recovered models that have been the main models for epidemics so far.

From Crowd Dynamics to Crowd Safety: A Video-Based Analysis

Anders Johansson and Dirk Helbing, Habib Z. Al-Abideen and Salim Al-Bosta

Abstract

The study of crowd dynamics is interesting because of the various self-organization phe- nomena resulting from the interactions of many pedestrians, which may improve or ob- struct their flow. Besides formation of lanes of uniform walking direction and oscillations at bottlenecks at moderate densities, it was recently discovered that stop-and-go waves [D. Helbing et al., Phys. Rev. Lett. 97, 168001 (2006)] and a phenomenon called “crowd turbulence” can occur at high pedestrian densities [D. Helbing et al., Phys. Rev. E 75, 046109 (2007)]. Although the behavior of pedestrian crowds under extreme conditions is decisive for the safety of crowds during the access to or egress from mass events as well as for situations of emergency evacuation, there is still a lack of empirical studies of extreme crowding. Therefore, this paper discusses how one may study high-density conditions based on suitable video data. This is illustrated at the example of pilgrim flows entering the previous Jamarat Bridge in Mina, 5 kilometers from the Holy Mosque in Makkah, Saudi-Arabia. Our results reveal previously unexpected pattern formation phenomena and show that the average individual speed does not go to zero even at local densities of 10 persons per square meter. Since the maximum density and flow are different from measurements in other countries, this has implications for the capac- ity assessment and dimensioning of facilities for mass events. When conditions become congested, the flow drops significantly, which can cause stop-and-go waves and a fur- ther increase of the density until critical crowd conditions are reached. Then, “crowd turbulence” sets in, which may trigger crowd disasters. For this reason, it is important to operate pedestrian facilities sufficiently below their maximum capacity and to take measures to improve crowd safety, some of which are discussed in the end.

ON THE MODELLING CROWD DYNAMICS FROM SCALING TO HYPERBOLIC MACROSCOPIC MODELS

NICOLA BELLOMO, CHRISTIAN DOGBÉ

Abstract

This paper, that deals with the modelling of crowd dynamics, is the first one of a project finalized to develop a mathematical theory refereing to the modelling of the complex sys- tems constituted by several interacting individuals in bounded and unbounded domains. The first part of the paper is devoted to scaling and related representation problems, then the macroscopic scale is selected and a variety of models are proposed according to different approximations of the pedestrian strategies and interactions. The second part of the paper deals with a qualitative analysis of the models with the aim of analyzing their properties. Finally, a critical analysis is proposed in view of further development of the modelling approach. Additional reasonings are devoted to understanding the conceptual differences between crowd and swarm modelling.

Crowd analysis: a survey

Beibei Zhan · Dorothy N. Monekosso ·Paolo Remagnino · Sergio A. Velastin · Li-Qun Xu

Abstract

In the year 1999 the world population reached 6 billion, doubling the previous census estimate of 1960. Recently, the United States Census Bureau issued a revised forecast for world population showing a projected growth to 9.4 billion by 2050 (US Census Bureau, http://www.census. gov/ipc/www/worldpop.html). Different research disci- plines have studied the crowd phenomenon and its dynamics from a social, psychological and computational standpoint respectively. This paper presents a survey on crowd analysis methods employed in computer vision research and discusses perspectives from other research disciplines and how they can contribute to the computer vision approach.

Validation of Crowd Models Including Social Groups

Gerta Köster, Franz Treml, Michael Seitz, and Wolfram Klein

Abstract

The development of group models within models of pedestrian motion has recently become a new focus of research. This interest was triggered by insight from the social sciences: Small groups often dominate the crowd at large events and the need to associate with family and friends may dominate over flight instincts. It is therefore desirable that crowd simulators adopt the new group models to better mitigate risks for example at large events or at public infrastructures. However, to make this feasible reliable validation tests must be made available. Developers and users alike should be able to check whether the adopted model indeed captures the essential characteristics of a crowd composed of subgroups. As a desirable side effect, common validation tests would make simulation tools easier to compare and their range of application easier to assess. This can help to ensure a minimum quality standard and thus to further mitigate risks. In this paper we suggest basic visual tests and some quantitative test were data is available.

An Agent-based Simulation System for Concert Venue Crowd Evacuation Modeling in the Presence of a Fire Disaster

Neal Wagner, Vikas Agrawal

Abstract

A key activity in emergency management is planning and preparation for disaster. If the right safety measures are implemented beforehand, harmful effects can be significantly mitigated. However, evaluation and selection of effective measures is difficult due to the numerous scenarios that exist in most emergency environments coupled with the high associated cost of test- ing such scenarios. An agent-based system employs a computational model of autonomous interacting agents in an environment with the purpose of as- sessing the emergent behavior of the group. This paper presents a prototype of a computer simulation and decision support system that uses agent-based modeling to simulate crowd evacuation in the presence of a fire disaster and provides for testing of multiple disaster scenarios at virtually no cost. The prototype is unique in the current literature as it is specifically designed to simulate a concert venue setting such as a stadium or auditorium and is highly configurable allowing for user definition of concert venues with any arrangement of seats, pathways, stages, exits, and people as well as the definition of multiple fires with fire and smoke dynamics included.

Modeling Crowd and Trained Leader Behavior during Building Evacuation

Nuria Pelechano and Norman I. Badler

Many applications can benefit from ani- mated virtual crowds. These applications include site planning, education, entertainment, training, and human factors analysis for building evacuation, or other scenarios where masses of people gather such as sporting events, transportation centers, and concerts.

A Crowd Evacuation System in Emergency Situation Based on Dynamics Model

Qianya Lin, Qingge Ji, and Shimin Gong

Abstract

This paper presents a system for crowd evacuation in emergency situation based on dynamics model to offer a base platform for further researches. Starting with the implementation of base functions, our focus is on the stability and expandable of the platform to offer new functions easily according to our needs latter. To improve the independence of the module, the function into layers and dividing the data are separated into blocks. To reach efficient system implementation, the 3D building is translated into a 2D graphics by turning the map into a group of nodes. Furthermore, the element called node plug is used to enhance the expansibility of the system. Experiments are carried out to analyze the crowd’s evacuation efficiency in a given building. The impact caused by mass behavior, the structure of the building and the number of people inside are also construed qualitatively in the experiments.

Human relationship modeling in agent-based crowd evacuation simulation

M Okaya, T Takahashi

Abstract

Not included in this link

Erfan Shahabpoor, Aleksandar Pavic, Vitomir Racic

Abstract

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual’s single-degree-of-freedom (SDOF) mass-spring-damper model using ‘reverse engineering’ methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Survey of detection techniques, mathematical models and simulation software in pedestrian dynamics

C. Caramuta, G. Collodel, C. Giacomini, C. Gruden, P. Piccolotto

Abstract

The study of pedestrian dynamics has become in the latest years an increasing field of research. A relevant number of technicians have been looking for improving technologies able to detect walking people in various conditions. Several researchers have dedicated their works to model walking dynamics and general laws. Many studiers have developed interesting software to simulate pedestrian behavior in all sorts of situations and environments. Nevertheless, till nowadays, no research has been carried out to analyze all the three over-mentioned aspects. The remarked lack in literature of a complete research, pointing out the fundamental features of pedestrian detection techniques, pedestrian modelling and simulation and their tight relationships, motivates the draft of this paper.

Aim of the paper is, first, to provide a schematic summary of each topic. Secondly, a more detailed description of the subjects is displayed, pointing out the advantages and disadvantages of each detection technology, the working logic of each model, outlining the inputs and the provided outputs, and the main features of the simulation software. Finally, the obtained results are summarized and discussed, in order to outline the correlation among the three explained themes.

Demand for Agent-Based Transportation Models & Social Behavioral Challenges

Samar El-Amine, Stéphane Galland, Ansar-Ul-Haque Yasar, Abderraffiaa Koukam

Abstract

Agent-Based modelling has been around us for quite some time now and has thus become a crucial factor for executing prediction-based planning, such as the transportation models for metropolitan cities. This paper undertakes the fundamental understanding of the agent-based modeling and simulation and its application to the transportation models while discussing the scope of its applications and advantages too. The paper then presents the concepts attributed to the social behaviors in conjunction with the agent-based modelling techniques applied so far. The literature review conducted in lieu of this work has resulted in agreement with the fact that the potential of agent-based modelling is by far greater than ever due to the ever-improving computing speeds and capabilities, while the understanding of complex human behavior will continue to be a challenge for simulations and automation techniques developed so far.

A Risk-based Model of Evacuation Route Optimization under Fire

Jing-jing Li, Hong-ya Zhu

Abstract

Emergency evacuation plan plays a key role for fire risk management and successful evacuation. In this work, a topological model of evacuation routes is established and the corresponding matrix function is also proposed in order to evaluate evacuation ability. Simultaneously, risk assessment of fire scenarios is made based on numerical simulation. And on this basis, the variation laws of risk indicators such as temperature, thermal radiation, the concentration of toxic gas are analyzed in details and dynamic risk assessment of evacuation routes is made. Introducing the concept of equivalent routes, the scheme of the best route for evacuee at each location is the one along with the shortest time and minimal risk and suggested based on the Dijkstra algorithm. And then, one case is presented and result indicates that this model can aid people to avoid crowdedness and evacuate as soon as possible under fire accident. The risk-based model is also useful for the evacuation planning.

Evacuation Models and Disaster Psychology

Harrie C.M. Vorst

Abstract

In evacuation models of buildings, neighborhoods, areas, cities and countries important psychological parameters are not frequently used. In this paper the relevance of some important variables from disaster psychology will be discussed. Modeling psychological variables will enhance prediction of human behavior during evacuations.
John Leach’s Dynamic Disaster Model describes three phases and five stages: A Pre-impact phase (Threat Stage and Warning Stage), an Impact phase, and a Post-impact phase (Recoil Stage, Rescue Stage and Post-traumatic Stage). In each phase and stage specific human behavior has been supposed to be a psychological response to a disaster. These responses are remarkably consistent and transferable across kinds of disasters.

Evacuation happens during Pre-impact phase, Impact phase and Post-impact phase (Recoil Stage and, or Rescue Stage). People’s cognitive and emotional states and overt behavior will be very different across the phases. During the Pre-impact phase risk estimation is very low, so evacuation is not seen as an inevitable action. Heavy stress and denial of life-threatening events during the Impact phase will hinder effective evacuation. Inactivity, apathy and childlike dependency on other people during the Recoil Stage will restrain survivors from active evacuation.

Evacuation models will be more effective if phases and accompanying human behavior are taken into account.

Modeling Pedestrian Dynamics with Adaptive Cellular Automata

Djalma Padovan, João José NetoPaulo Roberto Massa Cereda

Abstract

This work presents a proposal for modeling pedestrian dynamics by means of Adaptive Cellular Automata, a dynamically adjustable approach that uses an underlying cellular automata and a set of adaptive functions intended to reconfigure the automata internal structure and behavior according to observable events and rules, making them adaptable to environment changes.

Selain Kasereka, Nathanaël Kasoro, Kyandoghere Kyamakya, Emile-Franc Selain Kasereka,  Doungmo Goufo, Abiola P. Chokki, Maurice V.

Abstract

The evacuation of people from a building on fire is a task which can prove to be very difficult, in particular because of the influence of human behavior, but also of the type of people or the evacuation place configuration. Thus, it is crucial to think on how to organize the evacuation upstream for a situation of emergency can give rise disorganization, on one hand because of panic which grips evacuees, and on the other end because of the large quantity of evacuees in dangerous conditions. These recent years, several fire evacuation models have been proposed. Unfortunately, most of these models do not clearly define the parameters to be considered for their effective evaluations. These models consider, more generally, the number of survivors as a key parameter of evaluation. The purpose of this paper is to propose an intelligent Agent-Based Model enabling the modelling and simulation of evacuation of people from a building on fire. Our proposed model is based on four parameters that allow her practical evaluation. A case study of simulation is carried out in a building having the general configuration of Kinshasa supermarkets. This model is general enough for it to be implemented in several types of commercial buildings without major changes.

Analysis of the crowd evacuation modeling approaches for the case of urban underground spaces

Despina Papakonstantinou, Andreas Benardos, Anastasios Kallianiotis, Maria Menegaki,

Abstract

The growing need for more and more complicated underground urban systems has resulted to the development of a challenging environment for the setting up of effective evacuation procedure. The special circumstances and complexity, which characterize the underground spaces, as well as the severity of the consequences if an accident occurs, stimulated the research for different evacuation approaches in urban environments, in order to improve the efficiency of emergency evacuation and prevent crowd casualties in potential accidents, especially in the case of fire. The paper presents the most well respected standards, guidelines and regulations enforced worldwide, aiming to preserve the safeguarding of life and property against fire, explosion, and related hazards associated with developed subterranean spaces. Moreover, the evolution of underground evacuation approaches, from prescriptive methods to contemporary performance methods is displayed, followed by the examination of the approaches in crowd evacuation practices. Finally, the paper presents and analyses the factors being taken into account for planning the evacuation process, as illustrated through cases where modeling is conducted with special software codes.

Human factors in evacuation simulation, planning, and guidance

Gesine Hofinger, Robert Zinke, Laura Künzer

Abstract

Evacuation research shows growing interest in human factors and psychology. Before, humans were mostly modelled as homogeneous, without individual emotion, motivation or physical needs. Human factors had mainly been taken into account as physical characteristics or space requirements. In this paper, we give examples of relevant human factors from the literature and our own field research. Human factors include physical, cognitive, motivational and social variables. As yet, there is no validated set of variables most relevant for safe and fast evacuation. Models for classifying human factors from other domains are introduced for use in future research.

Dynamics-Based Stranded-Crowd Model for Evacuation in Building Bottlenecks

Lidi Huang, Deming Liu, and Yongyi Zhang

In high-density public buildings, it is di cult to evacuate. So in this paper, we propose a novel quantitative evacuation model to insure people’s safety and reduce the risk of crowding. We analyze the mechanism of arch-like clogging phenomena during evacuation and the in uencing factors in emergency situations at bottleneck passages; then we design a model based on crowd dynamics and apply the model to a stadium example. e example is used to compare evacuation results of crowd density with di erent egress widths in stranded zones. e results show this model proposed can guide the safe and dangerous egress widths in performance design and can help evacuation routes to be selected and optimized.

Application of Mathematical Model of Evacuation for Large Stadium Building

Bing Zhang

Abstract:

The statistics of sports arena accidents show that the main reasons which leading to crowd stampede are the exports blockage and the poor surrounding transportations. In the process of evacuation, the most common problem is that there are a large number of people are stranded and also they are the main carrier which leading to crowded stampede. With large amounts of data and reasonable evaluations on staffs and transportation instruments. We propose inflow model in the crowding state, principle of maximum flow on channel design, optimal model of vehicle parking, evacuation model of subways and buses, according to sections of evacuation in stadiums. We analyze their usage area, marginal conditions and real data. Finally, we get some valuable results, which are curves of density and flow, evacuation time, formula for channel design, optimal parking design and formulas for evacuation time of subways and buses. Such data suits the real data from varied references. With the help of models and results, we get the total time of evacuation, simulation of progress and give parts of real situations of evacuation. According to such results, 100000 people’s evacuation can be finished in about 45 min. On such basis, we propose some optimal plans for stadium and its surroundings building.

Survey of Holistic Crowd Analysis Models

Muhammad Taimoor Khan, Armughan Ali, Mehr Yahya Durrani, Imran Siddiqui

ABSTRACT

The behavior analysis techniques used in computer vision, are mostly targeting individual’s behavior. The study on crowd analysis is more focused on counting individuals and devising a management plan for load balancing for vehicles and pedestrians. The recent advancements in vision based techniques have allowed the study of collective behavior of the crowd for valuable information. It targets the application areas where crowds are dense making it impossible to segment individuals separately due to severe occlusion. Since object detection and identification techniques only works in low density crowds, therefore, holistic crowd analysis techniques are considered for this study. Holistic approach does not attempt to separate out the crowd and rather consider it as a single entity. It studies the behavior of the crowd, instead of the individual’s behavior. Recently available techniques for holistic crowd analysis are considered for this study. The working of these techniques is described and a comparative analysis is given to highlight their strengths and weaknesses.

Study of Evacuation Model for Multi-Functional Sports Stadium in Colleges

Haiyan Wang

Abstract:

The international universal calculations of the time for evacuation have their own features and limits and their effective areas have to be noticed. This study analyzes different ways to calculate the evacuation time, according to the relative indexes and rules for evacuation of Chinese sports stadium. According to the specific calculation in a university, it has safety hazards. On condition of not changing the hardware structures, this study proposes the notes and measures for safety evacuation and provides references and advice for its real application.

Context Ontology Modelling for Improving Situation Awareness and Crowd Evacuation from Confined Spaces

Gianluca Correndo, Banafshe Arbab-Zavar, Zlatko Zlatev, and Zoheir A. Sabeur

Abstract

Crowd evacuation management at large venues such as airports, stadiums, cruise ships or metro stations requires the deployment and access to a Common Operational Picture (COP) of the venue, with real-time intelligent contextual interpretation of crowd behaviour. Large CCTV and sensor network feeds all provide important but heterogeneous observations about crowd safety at the venue of interest. Hence, these observations must be critically analyzed and interpreted for supporting security managers of crowd safety at venues. Specifically, the large volume of the generated observations needs to be interpreted in context of the venue operational grounds, crowd-gathering event times and the knowledge on crowd expected behaviour. In this paper, a new context ontology modelling approach is introduced. It is based on knowledge about venue background information, expected crowd behaviours and their manifested features of observations. The aim is to improve situation awareness about crowd safety in crisis management and decision-support. © IFIP International Federation for Information Processing 2015.

Random Forces on Obstacles in Channels with Grains: A Mechanical Analogy
of Crowd Disasters

A. Medina, A. López-Villa and G. J. Gutiérrez

Abstract

In this work we have studied experimentally, through sensitive force measurements, the fluctuating forces on a rigid obstacle located at the middle of a horizontal channel, when a two-dimensional (2D) granular forced flow is induced by a wall-piston which moves with constant velocity along the channel. In this piston-like system, the force measured show strong fluctuations which are much larger than the average force, giving rise to intermittent behavior. Two different initial packing factors were employed, showing different flow characteristics. In the well-ordered high packing system, the force on the obstacle is very high, producing force peaks at time intervals almost constants. The main frequency is well correlated with the residence time of each row of grains. However, in case of initially disordered, loose packing systems, there is an initial relaxation time where force on the obstacle is extremely low, thus allowing the free flow of several grain rows. The temporal force traces have a \(1/\mathrm{f}^{\alpha }\) character and depend on the initial arrangement of grains.

Kincho H. Law, Ken Dauber and Xiaoshan Pan

Introduction
The objective of this research is to study humanand social behavior for emergency exit in
buildings and facilities. Among the numerous regulatory provisions governing a facility design,
one of the key issues identified by facility managers and building inspectors is safe egress. Design
of egress for places of public assembly is a formidable problem in facility and safety engineering.
There have been numerous incidents reported regarding overcrowding and crushing during
emergency situation. In addition to injuries and loss of lives, the accompanying post-disaster
psychological suffering, financial loss, and adverse publicity have long-term negative effects on
related individuals and organizations — the survivors, the victims’ families, and the local
communities [14]. In a crowded environment, it has been observed that most victims were
injured or killed by the so called “non-adaptive” behaviors of the crowd, rather than the actual
cause (such as fire) of the disaster [1,8]. Non-adaptive crowd behaviors refer to the destructive
actions that a crowd may experience during a disaster, such as stampede, pushing others out of
the way, knocking others down, and trampling on others, etc.; these actions are responsible for a
large number of injuries and, even, deaths in crowd disasters. To study the non-adaptive behavior
in a crowded environment, we need to carefully study human and behavior in panic situation from
both the psychological and sociological perspectives.

The Characteristics of the Factors that Govern the Preferred Force in the Social Force Model of Pedestrian Movement

Zarita Zainuddin, Mohammed Mahmod Shuaib, and Ibtesam M. Abu-Sulyman

Abstract

The social force model which belongs to the microscopic pedestrian studies has been considered as the supremacy by many researchers and due to the main feature of reproducing the self-organized phenomena resulted from pedestrian dynamic. The Preferred Force which is a measurement of pedestrian’s motivation to adapt his actual velocity to his desired velocity is an essential term on which the model was set up. This Force has gone through stages of development: first of all, Helbing and Molnar (1995) have modeled the original force for the normal situation. Second, Helbing and his co-workers (2000) have incorporated the panic situation into this force by incorporating the panic parameter to account for the panic situations. Third, Lakoba and Kaup (2005) have provided the pedestrians some kind of intelligence by incorporating aspects of the decision-making capability. In this paper, the authors analyze the most important incorporations into the model regarding the preferred force. They make comparisons between the different factors of these incorporations. Furthermore, to enhance the decision-making ability of the pedestrians, they introduce additional features such as the familiarity factor to the preferred force to let it appear more representative of what actually happens in reality.

Homogeneity and activeness of crowd on aged pedestrian dynamics

Jun Zhanga, Shuchao Caob, Daniel Saldena, Jian Ma

Abstract

An aging population is bringing new challenges to the management of escape routes and facility design in many countries. In this paper the movement properties of middle- and old-aged adults are studied with series of single-file movement experiments under laboratory conditions. The fundamental diagrams for two different groups of pedestrians and time-space diagrams are compared. For the groups with different composition and status, the fundamental diagrams are totally different but maintain the same trend. Active crowd leads to inhomogeneous pedestrian flow but higher flow rate, while inactive pedestrians prefer to keep pace with others or keep larger personal space, which leads to more jams and stop-and-go waves. Density and inhomogeneous of speed do not always play main roles on the appearance of stop-and-go.

Discrete Element Crowd Model for Pedestrian Evacuation Through an Exit

Peng Lina, Jian Mab and Siuming Lo

Abstract

A series of accidents caused by crowd within the last decades evoked a lot of scientific interest in modeling the movement of pedestrian crowds. Based on discrete element method, a granular dynamic model, in which human body is simplified as self-driven sphere, is proposed to simulate the characteristics of crowd flow through an exit. In this model, the repulsive force among people is considered to have an anisotropic feature, and the physical contact force due to body deformation is quantified by the Hertz contact model. The movement of human body is simulated by applying the second Newton’s law. The crowd flow through an exit at different desired velocities is studied and simulation results indicated that crowd flow exhibits three distinct states, i.e., smooth state, transition state and phase separation state. In the simulation, clogging phenomenon occurs more easily when the velocity of desired is high and the exit may as a result be totally blocked at a desired velocity of 1.6m/s or above, leading to faster-to-frozen effect.

Front-to-back communication in a microscopic crowd model

Colin Marc Henein and Tony White

Abstract

Failures in front-to-back communication (F2BC) in crowd disasters are commonly cited, but mechanisms and effects of F2BC have not been studied. We develop a plausible characterization and model of F2BC and evaluate it in a simple scenario. To study F2BC in a naturalistic context we then reconstruct a consistent geometry for the Who concert disaster, explore the mechanisms for that disaster, and introduce F2BC. Our qualitative analysis suggests that F2BC can reduce injuries at the cost of lower exit rates.

New Models for Crowd Dynamics and Control

Sadeq J. Al-nasur

Abstract

In recent years, there has been an increasing interest in modeling crowd and evacuation dynamics. Pedestrian models are based on macroscopic or microscopic behavior. In this work, we are interested in developing models that can be used for evacuation control strate- gies. Hence, we use macroscopic modeling approach, where pedestrians are treated in an aggregate way and detailed interactions are overlooked. In this dissertation, we developed two-dimensional space crowd dynamic models to allow bi-directional flow by modifying and enhancing various features of existing traffic and fluid dynamic models. In this work, four models based on continuum theory are developed, and conservation laws such as the conti- nuity and momentum equations are used. The first model uses a single hyperbolic partial differential equation with a velocity-density relationship, while the other three models are systems of hyperbolic partial differential equations. For one of the system models presented, we show how it can be derived independently from a microscopic crowd model. The mod- els are nonlinear, time-varying, hyperbolic partial differential equations, and the numerical simulation results given for the four macroscopic models were based on computational fluid dynamics schemes.

We also started an initial control design that synthesizes the feedback linearization method for the one-dimensional traffic flow problem applied directly on the distributed parameter system. In addition, we suggest and discuss the information technology requirements for an evacuation system.

Continuum Crowds

Adrien Treuille  Seth Cooper  Zoran Popovic

Abstract

We present a real-time crowd model based on continuum dynamics. In our model, a dynamic potential field simultaneously integrates global navigation with moving obstacles such as other people, effi- ciently solving for the motion of large crowds without the need for explicit collision avoidance. Simulations created with our system run at interactive rates, demonstrate smooth flow under a variety of conditions, and naturally exhibit emergent phenomena that have been observed in real crowds.

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

Hamed Faroqi ,  , Mohammad-Saadi Mesgari

Abstract

During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

Crowd-driven Mid-scale Layout Design 

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

Abstract

We propose a novel approach for designing mid-scale layouts by optimizing with respect to human crowd properties. Given an in- put layout domain such as the boundary of a shopping mall, our approach synthesizes the paths and sites by optimizing three met- rics that measure crowd flow properties: mobility, accessibility, and coziness. While these metrics are straightforward to evaluate by a full agent-based crowd simulation, optimizing a layout usually re- quires hundreds of evaluations, which would require a long time to compute even using the latest crowd simulation techniques. To overcome this challenge, we propose a novel data-driven approach where nonlinear regressors are trained to capture the relationship between the agent-based metrics, and the geometrical and topolog- ical features of a layout. We demonstrate that by using the trained regressors, our approach can synthesize crowd-aware layouts and improve existing layouts with better crowd flow properties.

How do people queue? A study of different queuing models

TGF 2015 Delft, 28th October 2015

No Abstract – Slide package

AUTONOMOUS TAWAF CROWD SIMULATION

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

Abstract

One of the most famous approaches to simulate a large density crowd is byapplying the social force model. This model can be successfully used to simulate agents’movement in real-world scenarios realistically. Nevertheless, this is very simple and not suitable to simulate a complex pedestrian flow movement. Hence, this research proposes anew novel model for simulating the pilgrims’ movements circling the Kaabah (Tawaf). These rituals are complex yet unique, due to its capacity, density, and various demographics backgrounds of the agents (pilgrims). It also had a certain set of rules and regulations that must be followed by the agents. Due to these rules, the Tawaf can introduce irregularities in the motion flow around the Kaabah. In order to make the simulation realistically, each agent will be assigned with different attributes such as; age, gender and intention outlook. The three parameters mentioned above, are the main problems that need to be solved in this research in order to simulate a better crowd simulation than previous studies. The findings of this research will contribute greatly for Hajj management in term of controlling and optimizing the flow of pilgrims during Tawaf especially in the Hajj season.

Modelling large-scale evacuation of music festivals

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

Abstract

This paper explores the use of multi-agent continuous evacuation modelling for representing large-scale evacuation scenarios at music festivals. A 65,000 people capacity music festival area was simulated using the model Pathfinder. Three evacuation scenarios were developed in order to explore the capabilities of evacuation modelling during such incidents, namely (1) a preventive evacuation of a section of the festival area containing approximately 15,000 people due to a fire breaking out on a ship, (2) an escalating scenario involving the total evacuation of the entire festival area (65,000 people) due to a bomb threat, and (3) a cascading scenario involving the total evacuation of the entire festival area (65,000 people) due to the threat of an explosion caused by a ship engine overheating. This study suggests that the analysis of the people-evacuation time curves produced by evacuation models, coupled with a visual analysis of the simulated evacuation scenarios, allows for the identification of the main factors affecting the evacuation process (e.g., delay times, overcrowding at exits in relation to exit widths, etc.) and potential measures that could improve safety.

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

Abstract

The aim of this paper is to investigate a simple model for simulating virtual crowds for virtual environments and computer games. This model is based on the Social Forces model and enhanced using Monte Carlo simulation. The focus is given on the behavior of the actual simulation. In this model we can see interactions between virtual agents (virtual pedestrians) in two scenarios, walking towards a path and crossroads. In both scenarios, these agents are avoiding each other, avoiding obstacles and walls in differ- ent scenarios like crossroad or narrowed street. Moreover, users can move, scale or rotate these obstacles and place them interactively into the scene.

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

Abstract

We present interactive algorithm to model physics-based interactions in dense crowds. Our approach is capable of modeling both physical forces and inter- actions between agents and obstacles, while also allow- ing the agents to anticipate and avoid upcoming col- lisions during local navigation. We combine velocity- based collision-avoidance algorithms with external phys- ical forces. The overall formulation produces various ef- fects of forces acting on agents and crowds, including balance recovery motion and force propagation through the crowd. We further extend our method to model more complex behaviors involving social and cultural rules. We use finite state machines to specify a series of behaviors and demonstrate our approach on many complex scenarios. Our algorithm can simulate a few thousand agents at interactive rates and can generate many emergent behaviors.

Crowd Art: Density and Flow Based Crowd Motion Design

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

Abstract

Artists, animation and game designers are in demand for solutions to easily populate large virtual environments with crowds that sat- isfy desired visual features. This paper presents a method to in- tuitively populate virtual environments by specifying two key fea- tures: localized density, being the amount of agents per unit of sur- face, and localized flow, being the direction in which agents move through a unit of surface. The technique we propose is also time- independant, meaning that whatever the time in the animation, the resulting crowd satisfies both features. To achieve this, our ap- proach relies on the Crowd Patches model. After discretizing the environment into regular patches and creating a graph that links these patches, an iterative optimization process computes the local changes to apply on each patch (increasing/reducing the number of agents in each patch, updating the directions of agents in the patch) in order to satisfy overall density and flow constraints. A specific stage is then introduced after each iteration to avoid the creation of local loops by using a global pathfinding process. As a result, the method has the capacity of generating large realistic crowds in minutes that endlessly satisfy both user specified densities and flow directions, and is robust to contradictory inputs. At last, to ease the design the method is implemented in an artist-driven tool through a painting interface.

TOWARD AN AGENT BASED DISTILLATION APPROACH FOR PROTESTING CROWD SIMULATION

Lam Thu BUI and Van Vien MAC

Abstract

This paper investigates the problem of protesting crowd simulation. It considers CROCADILE, an agent based distillation system, for this purpose. A model of protesting crowd was determined and then a CROCADILE model of protesting crowd was engineered and demonstrated. We validated the model by using two scenarios where protesters are varied with different personalities. The results indicated that CROCADILE served well as the platform for protesting crowd modeling simulation.

Crowds2D – a new, robust crowd dynamics simulation model

Steinar Børve

English summary

The Norwegian Armed Forces have over the last few years given priority to the procurement of less-lethal weapons (LLW) for use in certain scenarios. The purpose of FFI project 1255 has therefore been to support the armed forces in choosing the right means for different tactical scenarios and in a rapidly evolving marked. One class of scenarios where LLW can be a relevant tool involves human crowds. Choosing the right tool in such a scenario requires insight into the behaviour of human crowds.

The collective behaviour of human crowds is of interest not only to the armed forces, but also in civil applications such as pedestrian traffic studies, security planning of events involving large crowds, and police crowd management during political demonstrations and riots. The latter scenario is also relevant for the armed forces in operations abroad where peace-keeping and law- enforcement is an important part of the assigned task. In situations where law-enforces confront a crowd which include hostile or even violent individuals, one must decide whether or not to utilize LLW to control the crowd. The important question then is what can be achieved in a given scenario in terms of crowd management depending on whether LLWs are applied or not.

This report describes a new, robust crowd dynamics simulation model capable of simulating a wide range human crowd behaviour. It is a technical report and documents the important first steps towards a potentially useful tool in the analysis of LLW-related operations. This includes not only normal pedestrian traffic, but also scenarios such as evacuation or riots which might involve running agents. The model relies on a number of model parameters. Default values of these parameters have been determined on the basis of fundamental properties of the human body, semi-analytical models of fundamental crowd behaviour, and simplified crowd test simulations.

The new model not only captures crowd movement well, it also provide information on force levels which in turn can be used to assess the risk of injuries and deaths.

A Study of Modeling Crowd Dynamics

Andrew Fell

Abstract:

The following paper considers the field of Crowd Dynamics, and also the modeling thereof. This discipline has been becoming increasingly important in recent years and concerns itself with the propagation of pedestrian traffic in dense quarters. By considering such traffic flow a number of unique features and patterns can be discerned. Studied will be the current ‘state of the art’, and a modeling project based on one of the cited papers will be constructed and considered in further depth.

Modelling Crowd Dynamics During Evacuation Situations Using Simulation

Hugo Winter

Abstract

Evacuation of people during emergency situations is a crucial aspect when considering building design. Recently, numerous simulation methods have been constructed to provide insight during building development. The aim of this paper is to understand the causes of crowd disasters and review the simulation methods that are currently in use. Advantages and disadvantages of the different methods will be discussed as well as work that lies at the forefront of current research in this area.

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

Mehdi Moussaïd   Niriaska Perozo  Simon Garnier  Dirk Helbing  and  Guy Theraulaz

Abstract

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behavior consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium- scale aggregated structures and their impact on crowd dynamics is still largely unknown.

In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange.

These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.

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

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

Abstract.

This research aims for more understanding of behavior in crowds and riots. We state that crowd behavior can only be understood by studying the individuals and their interactions, a multi-level study. By selecting influence factors that influence the probability of a riot and translating this on how the individual is influenced, we have taken our first step in modeling and simulating human crowd behavior.

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

Gal Kaminka

Abstract

This report results from a contract tasking Bar Ilan University as follows: Accounting for Culture in Agent-Based Pedestrian Crowd Simulation
Accurate models of crowd dynamics are an important challenge in multi-agent systems and agent-based social simulation. Crowd models are able to predict the resulting macro level behavior from micro level interactions. However, many existing crowd models do not yet account for cultural factors in crowd behavior, and even more so, for crowds composed of members of different cultures. In this paper we examine the impact of cultural differences on the crowd dynamics in pedestrian and evacuation domains. In the pedestrian domain we relate to recorded pedestrian data in five different countries: Iraq, Israel, England, Canada and France and characterize these cultures based on cultural attributes at the individual level: personal spaces, speed, avoidance side and group formations. We use an agent-based simulation to investigate the impact on the resulting macro level behavior, such as pedestrian flow, number of collisions, etc. We also examine the impact of mixed-culture pedestrians on the resulting macro-level behavior. We quantitatively validate the simulation against data from movies of human crowds, in different countries. In the evacuation domain, we use an established simulation system to investigate cultural differences reported in the literature, and additionally explore the resulting macro level behavior.

A STUDY OF SIMULATION MODEL FOR PEDESTRIAN MOVEMENT WITH EVACUATION AND QUEUING

Shigeyuki Okazaki and Satoshi Matsushita

Abstract

The objective of this study is the development of a computer simulation model for

pedestrian movement in architectural and urban space. The characteristic of the model is the ability to visualize the movement of each pedestrian in a plan as an animation. So architects and designers can easily find and understand the problems in their design projects.

In this model, the movement of each pedestrian is simulated by the motion of a magnetized object in a magnetic field. Positive magnetic pole is given to each pedestrian and obstacles like walls and columns. Negative magnetic pole is located at the goal of pedestrians. Each pedestrian moves to his goal by the attractive force caused by the negative magnetic pole at his goal, avoiding collisions with other pedestrians and ob- stacles by repulsive forces caused by the positive magnetic poles.

The effectiveness of the simulation model is shown by the following two kinds of simulation examples.
(1) Evacuation from an office building

In this model pedestrians walk along the route from each starting point to the exit in case of evacuation. The example shows the places where stagnations and heavy conges- tions occur, and designers can see if the evacuation routes are appropriate.
(2) Movement of pedestrians in queue spaces

Three types of queuing behavior is classified in this model: movement in front of counters, movement passing through ratches, and movement of getting on and off in elevator halls. Simulation examples in a railway station and in a main floor of a resort hotel are shown where several kinds of queue spaces are included and complicated movements of hundreds of pedestrians occur.

 Human exit route choice in virtual crowd evacuations

Nikolai W.F.Bode, Edward A.Codling

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. This is crucial for the control of emergency evacuations from confined spaces, for example. At a microscopic level we seek to predict the next step of pedestrians based on their local environment. However, we also have to consider ‘tactical-level’ individual behaviour that is not an immediate response to the local environment, such as the choice between different routes to exit a building. We used an interactive virtual environment to study human exit route decisions in simulated evacuations. Participants had to escape from a building and had to choose between different exit routes in the presence of evacuating simulated agents. We found no inherent preference for familiar routes, but under a stress-inducing treatment, subjects were more likely to display behaviour in their route choice that was detrimental to their evacuation time. Most strikingly, subjects were less likely to avoid a congested exit by changing their original decision to move towards it under this treatment. Age and gender had clear effects on reaction times in the virtual environment.

Discrete choice models of pedestrian walking behaviour

Gianluca Antonini ,Michel Bierlaire , Mats Weber

Abstract

We propose a discrete choice framework for pedestrian dynamics, modelling short term behavior of individuals as a response to the presence of other pedestrians. We use a dynamic and individual-based spatial discretization, representing the physical space. We develop a model predicting where the next step of a walking pedestrian will be, at a given point in time. The use of the discrete choice framework is justified by its flexibility, the capacity to deal with individuals and the compatibility with agent-based simulation. The model is calibrated using data from actual pedestrian movements, manually taken from video sequences. We present two different formulations: a cross-nested logit and a mixed nested logit. In order to verify the quality of the calibrated model, we have designed and developed a pedestrians simulator.

Dynamic decision making: Human control of complex systems

Berndt Brehmer

Abstract

This paper reviews research on dynamic decision making, i.e., decision making under conditions which require a series of decisions, where the decisions are not independent, where the state of the world changes, both autonomously and as a consequence of the decision maker’s actions, and where the decisions have to be made in real time. It is difficult to find useful normative theories for these kinds of decisions, and research thus has to focus on descriptive issues. A general approach, based on control theory, is proposed as a means to organize research in the area. An experimental paradigm for the study of dynamic decision making, that of computer stimulated microworlds, is discussed, and two approaches using this paradigm are described: the individual differences approach, typical of German work in the tradition of research on complex problem solving, and the experimental approach. In studies following the former approach, the behavior of groups differing in performance is compared, either with respect to strategies or with respect to performance on psychological tests. The results show that there are wideinterindividual differences in performance, but no stable correlations between performance in microworlds and scores on traditional psychological tests have been found. Experimental research studying the effects of system characteristics, such as complexity and feedback delays, on dynamic decision making has shown that decision performance in dynamic tasks is strongly affected by feedback delays and whether or not the decisions have side effects. Although neither approach has led to any well-developed theory of dynamic decision making so far, the results nevertheless indicate that we are now able to produce highly reliable experimental results in thelaboratory, results that agree with those found in field studies of dynamic decision making. This shows that an important first step towards a better understanding of these phenomena has been taken.

Simulation of pedestrian dynamics using a two-dimensional cellular automaton

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

Abstract

We propose a two-dimensional cellular automaton model to simulate pedestrian traffic. It is a vmax=1 model with exclusion statistics and parallel dynamics. Long-range interactions between the pedestrians are mediated by a so-called floor field which modifies the transition rates to neighbouring cells. This field, which can be discrete or continuous, is subject to diffusion and decay. Furthermore it can be modified by the motion of the pedestrians. Therefore, the model uses an idea similar to chemotaxis, but with pedestrians following a virtual rather than a chemical trace. Our main goal is to show that the introduction of such a floor field is sufficient to model collective effects and self-organization encountered in pedestrian dynamics, e.g. lane formation in counterflow through a large corridor. As an application we also present simulations of the evacuation of a large room with reduced visibility, e.g. due to failure of lights or smoke.

Consensus decision making in human crowds

JOHN R. G. DYER*, CHRISTOS C. IOANNOU*, LESLEY J . MORRELL*, DARREN P. CROFT*,AIN D. COUZIN‡§, DEAN A. WATERS* & JENS KRAUSE*

Abstract

In groups of animals only a small proportion of individuals may possess particular information, such as a migration route or the direction to a resource. Individuals may differ in preferred direction resulting in conflicts of interest and, therefore, consensus decisions may have to be made to prevent the group from splitting. Recent theoretical work has shown how leadership and consensus decision making can occur without active signalling or individual recognition. Here we test these predictions experimentally using humans. We found that a small informed minority could guide a group of naïve individuals to a target without verbal communication or obvious signalling. Both the time to target and deviation from target were decreased by the presence of informed individuals. When conflicting directional information was given to different group members, the time taken to reach the target was not significantly increased; suggesting that consensus decision making in conflict situations is possible, and highly efficient. Where there was imbalance in the number of informed individuals with conflicting information, the majority dictated group direction. Our results also suggest that the spatial starting position of informed individuals influences group motion, which has implications in terms of crowd control and planning for evacuations.

Leadership and social information use in human crowds

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

Abstract

One of the big challenges for group-living animals is to find out who in a group has pertinent information (regarding food or predators) at any moment in time, because informed individuals may not be obviously recognizable to other group members. We found that individuals in human groups were capable of identifying those with information, and this identification increased group performance: the speed and accuracy of groups in reaching a target. Using video analysis we found how informed individuals might have been identified by other group members by means of inadvertent social cues (such as starting order, time spent following and group position). Furthermore, we were able to show that at least one of these cues, the group position of informed individuals, was indeed correlated with group performance. Our final experiment confirmed that leadership was even more efficient when the group members were given the identity of the leader. We discuss the effect of information status regarding the presence and identity of leaders on collective animal behaviour.

Crossing at a red light: Behaviour of individuals and groups

Tova Rosenbloom

Abstract

The present study examines the road behaviour of individual pedestrians at an intersection with a traffic signal compared to groups of pedestrians at the same intersection.

In total, 1392 pedestrians were unobtrusively observed in an urban setting at a pedestrian street crossing of undivided streets; 842 were female (60.5%) and 550 were male (39.5%). The observations took place between 7:30 and 8:30 in the morning. Chi-square test revealed the males crossed on red more frequently than females. Logistic regression predicting red-light crossing for pedestrians arriving during a red-light phase indicated that, apart from gender, the tendency to cross on red was greater when there were fewer people waiting at the curb, either when a pedestrian arrived, or joining after arrival. The discussion refers to the theoretical explanations concerning the theory of ‘social control’ and to some practical implications of the results, such as using the positive value of social control in media campaigns and adjusting the red light duration in order to encourage people to obey the traffic light.

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

Abstract

A bidimensional cellular automaton model is used to simulate the process of evacuation of pedestrians in a room with fixed obstacles. A floor field is defined so that moving to a cell with lower floor field means approaching an exit door. The model becomes non-deterministic by introducing a “panic” parameter, given by a probability of not moving, and by a random choice to resolve conflicts in the update of pedestrian positions. Two types of exit doors are considered: single (where only one person can pass) and double (two persons can pass simultaneously). For a double door, the longest evacuation time turns out to occur for a very traditional location of the door. The optimum door position is determined. Replacing the double door by two single doors does not improve evacuation times noticeably. On the other hand, for a room without obstacles, a simple scaling law is proposed to model the dependence of evacuation time with the number of persons and exit width. This model fails when obstacles are present, as their presence introduces local bottlenecks whose effect outweighs the benefits of increasing door width beyond a certain threshold.

Crowd Simulation for Dynamic Environments based on Information Spreading and Agents’ Personal Interests

Konrad Jablonski, Vasileios Argyriou, Darrel Greenhill

Abstract

In this work a novel crowd simulation framework that incorporates information of the dynamic environment is introduced. It supports knowledge spreading and allows the simulated agents to behave according to their personal needs that are affected by the surroundings. Each agent has their own personal interests and needs, which affects its goals and interactions with the environment. Genetic algorithms are used to simulate the dynamic behaviour of the environment and the knowledge spreading. As a result more accurate and realistic simulations are obtained improving a wide range of industrial and research applications that require accurate crowd simulation and modelling.

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

Neal Wagner, Vikas Agrawal

Abstract

A key activity in emergency management is planning and preparation for disaster. If the right safety measures are implemented beforehand, harmful effects can be significantly mitigated. However, evaluation and selection of effective measures is difficult due to the numerous scenarios that exist in most emergency environments coupled with the high associated cost of testing such scenarios. An agent-based system employs a computational model of autonomous interacting agents in an environment with the purpose of assessing the emergent behavior of the group. This paper presents a prototype of a computer simulation and decision support system that uses agent-based modeling to simulate crowd evacuation in the presence of a fire disaster and provides for testing of multiple disaster scenarios at virtually no cost. The prototype is unique in the current literature as it is specifically designed to simulate a concert venue setting such as a stadium or auditorium and is highly configurable allowing for user definition of concert venues with any arrangement of seats, pathways, stages, exits, and people as well as the definition of multiple fires with fire and smoke dynamics included.

A Simple and Realistic Pedestrian Model for Crowd Simulation and Application

Wonho Kang and Youngnam Han

Abstract

The simulation of pedestrian crowd that reflects reality is a major challenge for researches. Several crowd simulation models have been proposed such as cellular automata model, agent-based model, fluid dynamic model, etc. It is important to note that agent-based model is able, over others approaches, to provide a natural description of the system and then to capture complex human behaviors.
In this paper, we propose a multi-agent simulation model in which pedestrian positions are updated at discrete time intervals. It takes into account the major normal conditions of a simple pedestrian situated in a crowd such as preferences, realistic perception of environment, etc. Our objective is to simulate the pedestrian crowd realistically towards a simulation of believable pedestrian behaviors. Typical pedestrian phenomena, including the unidirectional and bidirectional movement in a corridor as well as the flow through bottleneck, are simulated. The conducted simulations show that our model is able to produce realistic pedestrian behaviors. The obtained fundamental diagram and flow rate at bottleneck agree very well with classic conclusions and empirical study results. It is hoped that the idea of this study may be helpful in promoting the modeling and simulation of pedestrian crowd in a simple way.

John Prpić  Prashant Shukla

Abstract

The increasing practice of engaging crowds, where organizations use IT to connect with dispersed individuals for explicit resource creation purposes, has precipitated the need to measure the precise processes and benefits of these activities over myriad different implementations. In this work, we seek to address these salient and non-trivial considerations by laying a foundation of theory, measures, and research methods that allow us to test crowd- engagement efficacy across organizations, industries, technologies, and geographies. To do so, we anchor ourselves in the Theory of Crowd Capital, a generalizable framework for studying IT-mediated crowd-engagement phenomena, and put forth an empirical apparatus of testable measures and generalizable methods to begin to unify the field of crowd science.

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

Bolei Zhou, Xiaogang Wang, and Xiaoou Tang

Slide presentation

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

S. R. Musse and D. Thalmann

Abstract

This paper presents a model of crowd behavior to simulate the motion of a generic population in a specific environment. The individual parameters are created by a distributed random behavioral model which is determined by few parameters. This paper explores an approach based on the relationship between the autonomous virtual humans of a crowd and the emergent behavior originated from it. We have used some concepts from sociology to represent some specific behaviors and represent the visual output. We applied our model in two applications: a graphic called sociogram that visualizes our population during the simulation, and a simple visit to a museum. In addition, we discuss some aspects about human crowd collision.

On the Mathematical Modeling and Simulation of Crowd Motion

Marie-Therese Wolfram

Slide presentation

A Cellular Automaton Model for Crowd Movement and Egress Simulation

Von der Fakulta ̈t 4 – Naturwissenschaften

Abstract

The movement of crowds is a field of research that attracts increasing interest. This is due to three major reasons: pattern formation and self- organization processes that occur in crowd dynamics, the advancement of simulation techniques and hardware that enable fast and realistic simulations, and finally the growing area of potential applications (planning of pedestrian facilities, crowd management, or evacuation analysis). The field is spanning the borders of various disciplines: physiology, psychology, sociology, civil en- gineering, mathematics, physics, etc. It depends on the point of view which aspects are given the main focus. One approach is to reduce complexity to fundamental principles that make a mathematical (quantitative) formulation possible and at the same time are sufficiently complex to reproduce the major phenomena that can be observed in reality.

The major aim of this dissertation is to define and validate a model for the simulation of evacuation processes and their analysis. To this end the analogy between non-equilibrium many particle systems and crowds is used. However, it will also become clear that this analogy is not sufficient for com- plex scenarios and realistic egress simulations and additional, ‘non-physical’, parameters and principles must be introduced. Even though the investiga- tion is motivated by the applications, the dynamics of crowd movement and model properties are scrutinized. This also includes a thorough review of the data available in the literature, the calibration of the model parameters and the comparison of simulated and empirical flow-density relations.

The core of any evacuation simulation is a set of rules or equations for the movement of people. This is connected to the representation of space, popu- lation, and behavior. These topics will be investigated generally (micro- vs. macroscopic, discrete vs. continuous) and especially with regard to a specific two-dimensional cellular automaton model, where the movement dynamics is based on discrete space and time. This allows an efficient implementation and therefore large scale simulations. The route-choice is done via the orientation along a discrete vector field which can in principal be derived from a discrete potential. It is therefore not explicitly simulated but taken into account in a pre-determined way, i.e., the coupling to the vector field is static (constant coupling parameter). In addition to the model characteristics, extensions like competition, multiple and dynamically varying orientation potentials or coupling parameters, or individual egress routes are discussed.

In order to validate the simulation results and the application to full-scale problems, simulations for realistic scenarios are performed and compared to data from evacuation trials. Design variants, aspects of crowd management, or operational measures to optimize evacuation performance are also men- tioned. However, they are the task of experts (architects, psychologists, safety engineers) who might use simulations as a design and evaluation tool. There- fore, these results are rather case studies supplementing the major topics of the model characteristics and implementation.

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

Funda Durupınar Jan Allbeck Nuria Pelechano Norman Badler

Abstract

Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naïve user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High- Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors.

A Crowd Behavior Model Based on Reciprocal Velocity Obstacle Algorithm

Xiaona Lia, Wenhu Qin

Abstract

A crowd behavior model based on reciprocal velocity obstacle algorithm is proposed in this paper. The model is the combination autonomous navigation and crowd behavior strategy module. Reciprocal Velocity Obstacle algorithm is adopted to achieve global path planning. individuals act quite differently under various circumstances, and several behavior strategies are applied in crowd simulation on the basis of social theory: in normal condition people show their humility confronting interaction, therefore they queue up with the application of stop rules; while in emergency circumstances, competition feature appears during inter-individual interactive process, as a result they decelerate towards their goals with the arching and congestion phenomena observed. The results show the good performance for crowd evacuation in real time and realism of the simulation process.

Bayesian Model Adaptation for Crowd Counts

Bo Liu Nuno Vasconcelos

Abstract

The problem of transfer learning is considered in the domain of crowd counting. A solution based on Bayesian model adaptation of Gaussian processes is proposed. This is shown to produce intuitive model updates, which are tractable, and lead to an adapted model (predictive dis- tribution) that accounts for all information in both train- ing and adaptation data. The new adaptation procedure achieves significant gains over previous approaches, based on multi-task learning, while requiring much less computa- tion to deploy. This makes it particularly suited for the prob- lem of expanding the capacity of crowd counting camera networks. A large video dataset for the evaluation of adap- tation approaches to crowd counting is also introduced. This contains a number of adaptation tasks, involving infor- mation transfer across video collected by 1) a single camera under different scene conditions (different times of the day) and 2) video collected from different cameras. Evaluation of the proposed model adaptation procedure in this dataset shows good performance in realistic operating conditions.

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

Yasser Ibrahim and Rasha Hassan

Since Le Bon introduced his profound theory about the crowd in 1895, the phenomenon has been investigated across a range of scientific disciplines. Nevertheless, the mystery of the popular mind seems so far unrevealed, especially with the emergence of unfamiliar crowd movements, such as Twitter revolutions, which are triggered by novel types of media and interpersonal communication. Such original collective behavior, along with the current turbulent sociopolitical global environment, has necessitated the development of explanatory contemporary models. This research introduces a new revolutionary crowd model with a unique set of internal and external factors that can fit the modern uprisings in order to enable the understanding of the conditions that could lead to or prohibit the formation of revolutionary crowds. The model is implemented to examine the effectiveness of oscillating intensified mass media on the crowd pattern and dynamics. Among several emergent behaviors, the model shows an insignificant impact of disrupted intensified media on the crowd, in contrast with consistent low-intensity media, the failure of contagion theory in sustaining a revolution without a persistent stimulus, and the refutation of current claims of the insignificancy of leaders’ roles in igniting and maintaining modern crowds.

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

Natalie Fridman and Gal A. Kaminka

Abstract

Models of crowd behavior facilitate analysis and prediction of human group behavior, where people are affected by each other’s presence. Unfortunately, existing models leave many open challenges. In particular, psychology models often of- fer only qualitative description, while computer science mod- els are often simplistic, and are not reusable from one sim- ulated phenomenon to the next. We propose a novel model of crowd behavior, based on Festinger’s Social Comparison Theory (SCT). We propose a concrete algorithmic framework for SCT, and evaluate its implementation in several crowd behavior scenarios. Results from task measures and human judges evaluation shows that the SCT model produces im- proved results compared to base models from the literature.

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

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

Abstract

To test simulation models of pedestrian flows, we have performed experiments for corridors, bottleneck areas, and intersections. Our evaluations of video recordings show that the geometric boundary conditions are not only relevant for the capacity of the elements of pedestrian facilities, they also influence the time gap distribution of pedestrians, indicating the existence of self-organization phenomena. After calibration of suitable models, these findings can be used to improve design elements of pedestrian facilities and egress routes. It turns out that “obstacles” can stabilize flow patterns and make them more fluid. Moreover, intersecting flows can be optimized, utilizing the phenomenon of “stripe formation.” We also suggest increasing diameters of egress routes in stadia, theaters, and lecture halls to avoid long waiting times for people in the back, and shock waves due to impatience in cases of emergency evacuation. Moreover, zigzag-shaped geometries and columns can reduce the pressure in panicking crowds. The proposed design solutions are expected to increase the efficiency and safety of train stations, airport terminals, stadia, theaters, public buildings, and mass events in the future. As application examples we mention the evacuation of passenger ships and the simulation of pilgrim streams on the Jamarat bridge. Adaptive escape guidance systems, optimal way systems, and simulations of urban pedestrian flows are addressed as well.

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

Abstract

We present an information-theoretic method to measure the similar- ity between a given set of observed, real-world data and visual sim- ulation technique for aggregate crowd motions of a complex system consisting of many individual agents. This metric uses a two-step process to quantify a simulator’s ability to reproduce the collective behaviors of the whole system, as observed in the recorded real- world data. First, Bayesian inference is used to estimate the sim- ulation states which best correspond to the observed data, then a maximum likelihood estimator is used to approximate the predic- tion errors. This process is iterated using the EM-algorithm to pro- duce a robust, statistical estimate of the magnitude of the prediction error as measured by its entropy (smaller is better). This metric serves as a simulator-to-data similarity measurement. We evalu- ated the metric in terms of robustness to sensor noise, consistency across different datasets and simulation methods, and correlation to perceptual metrics.

Agent-based Modeling of Crowd Dynamics on a Moving Platform

Dmitriy Rybokonenko, Marina Balakhontceva,

Abstract

This paper proposes a mathematical model and a computational approach applied to the study of the interaction between a moving platform and pedestrians walking on it. A ship deck motion used as a basic scenario for simulation is realized in three modes reproducing heaving, pitching or rolling rotations of the vessel. Behavior of virtual passengers is emulated by the Social Force pedestrian model modified with additional forces. In this paper the mathematical definitions of both models and their software implementations are discussed. The results of the experiments reproducing various combinations of characteristics of the ship motion are presented and compared with a case where it remained stationary. The paper is concluded with an analysis of the simulation results and perspectives for further research.

Counterflow Model for Agent-Based Simulation of Crowd Dynamics

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

Abstract

Agent-based crowd models describe pedestrians as autonomous interacting agents. Current models take into account the physical contact forces occurring in a crowd, but the description of many behavioural actions is still a challenge. This paper presents a model for agents’ behaviour in counterflow situations, where they try to avoid collisions with oncoming agents. In the model, the agents observe the walking directions of the agents in front of them and choose their own actions ac- cordingly. We implement the model to the widely used social force model, which describes the the motion of each agent in a Newtonian manner. Nevertheless, the basic idea of the counterflow model can be used with various modelling platforms. We study the effects of the model’s parameters with Monte Carlo simulations and justify our selection of their values. Simulation results are compared with previ- ously published experimental data and the results match well.

The Impact of Culture on Crowd Dynamics: An Empirical Approach

Natalie Fridman Gal, A. Kaminka, Avishay Zilka

ABSTRACT

In agent-based social simulation, crowd models are used to gener- ate agent behaviors that should correspond closely to human crowds. Despite significant progress in this area, many existing crowd mod- els do not yet account for important cultural factors in crowd behav- ior, and even more so, for mixed-culture crowds. Moreover, evalua- tion of crowd models accounting for culture is particularly difficult, e.g., as controlled experiments are more difficult to set up, due to lack of subjects from different cultures. In this paper we exam- ine the impact of cultural differences on crowd dynamics in pedes- trian and evacuation domains. We account for micro-level cultural attributes: personal spaces, speed, pedestrian avoidance side and group formations. We then quantitatively validate the macro-level predictions of an agent-based simulation utilizing these against data from web-cam movies of human pedestrian crowds recorded in five different countries: Iraq, Israel, England, Canada and France. Us- ing the validated simulations, we investigate the impact of each micro-level attribute on the resulting macro level behavior. We also examine the impact of mixed cultures on macro-level behavior. In the evacuation domain, we use an established simulation system to investigate cultural differences reported in the literature, and addi- tionally explore the resulting macro level behavior.

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

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

Abstract

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behavior consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium- scale aggregated structures and their impact on crowd dynamics is still largely unknown.

In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange.

These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.

Crowd Dynamics and Control in High-Volume Metro Rail Stations

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

Abstract

Overcrowding in mass rapid transit stations is a chronic issue affecting daily commute in Metro Manila, Philippines. As a high-capacity public transportation, the Metro Rail Transit has been operating at a level above its intended capacity of 350,000 passengers daily. Despite numerous efforts in implementing an effective crowd control scheme, it still falls short in containing the formation of crowds and long lines, thus affecting the amount of time before they can proceed to the platforms. A crowd dynamics model of commuters in one of the high-volume terminal stations, the Taft Ave station, was developed to help discover emergent behavior in crowd formation and assess infrastructure preparedness. The agent-based model uses static floor fields derived from the MRT3 live feed, and implements a number of social force models to optimize the path-finding of the commuter agents. Internal face validation, historical validation and parameter variability-sensitivity analysis were employed to validate the crowd dynamics model and assess different operational scenarios. It was determined that during peak hours, when the expected crowd inflow may reach up to 7,500 commuters, at least 11 ticket booths and 6 turnstiles should be open to have low turnaround times of commuters. For non-peak hours, at least 10 ticket booths and 5 turnstiles are needed to handle a crowd inflow reaching up to 5,000 commuters. In the current set-up, the usual number of ticket booths open in the MRT Taft Station is 11, and there are usually 6 turnstiles open. It was observed that as the crowd inside the station increases to 200-250 commuters, there is a significant increase in the increase rate of the turnaround times of the commuters, which signifies the point at which the service provided starts to degrade and when officials should start to intervene.

CROWD DYNAMICS AND CONSERVATION LAWS WITH NON–LOCAL CONSTRAINTS

BORIS ANDREIANOV, CARLOTTA DONADELLO, AND MASSIMILIANO D. ROSINI

Abstract.

In this paper we model pedestrian flows evacuating a narrow corridor through an exit by a one–dimensional hyperbolic conservation law with a non–local constraint. Existence and stability results for the Cauchy problem with Lipschitz constraint are achieved by a procedure that combines the wave–front tracking al- gorithm with the operator splitting method. The Riemann problem with piecewise constant constraint is discussed in details, stressing the possible lack of uniqueness, self–similarity and L1loc–continuity. One explicit example of application is provided.

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

Abstract

Perceiving crowd emotions and understand the sit- uation is vital to control the situations in surveillance appli- cations. This paper introduces the evolution of methods for crowd emotion perception based on bio-inspired probabilistic models. The emotions have been perceived both in an offline and online manner from the crowd. We focus on the perception of emotion from crowd behavior and dynamics. The paper explains few probabilistic algorithms and compares these for detection of emotion of crowds and proposes a probabilistic modelling approach which is trained on data to perceive the emotions of the crowd in an area under surveillance. Emotions are defined as evolving dynamic patterns arising due to interaction of people in an environment with their relationships to the past interaction patterns. Camera sensors are used to track the motion of the individuals within a crowd scenario under observation. The data mining techniques are used to distinguish between different behaviors and events into positive and negative emotions. The results have been evaluated using simulated data from a proposed office environment.

On the Mathematical Modeling and Simulation of Crowd Motion

Marie-Therese Wolfram

Slide presentation

MARTIN NYGREN

Abstract

The human being is a flocking animal and is often a member of a crowd. Because flocking is a large part of human life, human crowds is an interesting field of study. Crowds can often act in ways that seem irrational and unpredictable. This is however not the case. A crowd follows specific rules and though they may be hard to predict they can be simulated.

The focus of crowd behaviour research is often on massive crowds of several thousand members. In very large groups the freedom of the individuals is restricted and the human reasoning can often be omitted. This thesis presents a way of combining crowd behaviour simulating techniques with human behaviour simulating techniques. The combined human crowd behaviour model bridges the gap between crowd models that simulates very large groups with human models that simulates one individual. The new model aims to simulate medium sized groups of a few hundred members where the human reasoning affect the behaviour of the individuals and the whole crowd.

A human crowd behaviour model is presented in the paper. A simulator has been built based on the model and the results from the simulations performed on the simulator is presented as well.

The thesis concludes that it is possible to combine crowd behaviour techniques with human behaviour techniques and thereby solve some of the problems that appear when the techniques are used one by one. Furthermore, the thesis shows that the combined techinque is most beneficial when the crowd is sparse, the environment is complex and when the goals are nontrivial.

A Multi-agent Model for Panic Behavior in Crowds

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

Abstract.

This paper presents a conceptual model for the panic in crowds’ phenomenon. The proposed model is based on social science theories related to collective behavior. Such model could be applied in two dimensions: (i) to assist in proposing new structures or variations for collective panic situations, checking the viability of their existence and inner-working; (ii) to get a better understanding of social, anthro- pological and psychological foundations, etc. which drive and maintain the panic in crowds type of collective behavior. One of the challenges to be faced by this study is the integration of different theories in a co- herent and robust way, since many of them have contradictory positions. Besides, thanks to the fact that these theories show a higher degree of ab- straction, adjustments will be made in order to achieve the computability of the proposed conceptual model.

Hidden Markov Models for Optical Flow Analysis in Crowds

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

Abstract

This paper presents an event detector for emergencies in crowds. Assuming a single camera and a dense crowd we rely on optical flow instead of tracking statistics as a feature to extract information from the crowd video data. The optical flow features are encoded with Hidden Markov Models to allow for the detection of emergency or abnormal events in the crowd. In order to increase the detection sen- sitivity a local modelling approach is used. The results with simulated crowds show the effectiveness of the proposed ap- proach on detecting abnormalities in dense crowds.

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

Abstract

Large multi-agent systems such as crowds involve inter-agent interactions that are typically anticipatory in nature, depending strongly on both the positions and the velocities of agents. We show how the nonlinear, anticipa- tory forces seen in multi-agent systems can be made compatible with recent work on energy-based formulations in physics-based animation, and propose a simple and e ective optimization-based integration scheme for implicit integration of such systems. We apply this approach to crowd simulation by using a state-of-the-art model derived from a recent analysis of human crowd data, and adapting it to our framework. Our approach provides, for the rst time, guaranteed collision-free motion while simultaneously maintaining high-quality collective behavior in a way that is insensitive to simulation parameters such as time step size and crowd density. ese bene ts are demonstrated through simulation results on various challenging scenarios and validation against real-world crowd data.

Individual-Oriented Model Crowd Evacuations Distributed Simulation

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

Abstract

Emergency plan preparation is an important problem in building design to evacuate people as fast as possible. Simulation exercises as fire drills are not a realistic situation to understand people behaviour. In the case of crowd evacuations the complexity and uncertainty of the systems increases. Computer simulation allows us to run crowd dynamics models and extract information from emergency situations. Several models solve the emergency evacuation problem. Individual oriented modelling allows to give behaviour rules to the individual and simulate interactions between them. Due to variation on the emergency situations results have to be statistically reliable. This reliability increases the computing demand. Distributed and parallel paradigms solve the performance problem. In the present work we present a crowd evacuations distributed simulator. We implemented two versions of the model. One using Netlogo and another using C with MPI. We chose a real environment to test the simulator: pavilion 2 of Fira de Barcelona building, able to hold thousands of persons. The distributed simulator was tested with 62,820 runs in a distributed environment with 15,000 individuals. In this work we show how the distributed simulator has a linear speedup and scales efficiently.

Herding Model: Analysis and Numerical Simulations

By Martin Burger, Peter Markowich, Jan-Frederik Pietschmann

Abstract

In this paper we study the continuum limit of a cellular automaton model used for simulat- ing human crowds with herding behaviour. We derive a system of non-linear partial differential equations resembling the Keller-Segel model for chemotaxis, however with a non-monotone in- teraction. The latter has interesting consequences on the behaviour of the model solutions, which we highlight in its analysis. In particular we study the possibility of stationary states and the formation of clusters.

We also introduce an efficient numerical simulation approach based on appropriate hybrid discontinuous Galerkin, which in particular allow flexible treatment of complicated geometries. Extensive numerical studies also provide a better understanding the strengths and shortcomings of the herding model, in particular we examine trapping effects of crowds behind non-convex obstacles.

Modelling Crowd Scenes for Event Detection

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

Abstract

This work presents an automatic technique for detection of abnormal events in crowds. Crowd behaviour is difficult to predict and might not be easily semantically translated. Moreover it is difficulty to track individuals in the crowd using state of the art tracking algorithms. Therefore we characterise crowd behaviour by observing the crowd opti- cal flow and use unsupervised feature extraction to encode normal crowd behaviour. The unsupervised feature extrac- tion applies spectral clustering to find the optimal number of models to represent normal motion patterns. The mo- tion models are HMMs to cope with the variable number of motion samples that might be present in each observation window. The results on simulated crowds demonstrate the effectiveness of the approach for detecting crowd emergency scenarios.

Simulating Dynamical Features of Escape Panic

Dirk Helbing, Ill ́es Farkas and Tam ́as Vicsek

One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatal- ities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings;1,2 at other times, stampedes can arise from the rush for seats3,4 or seemingly without causes. Tragic examples within re- cent months include the panics in Harare, Zimbabwe, and at the Roskilde rock concert in Denmark. Although engineers are finding ways to alleviate the scale of such disasters, their frequency seems to be increasing with the number and size of mass events.2,5 Yet, systematic studies of panic behaviour,6−9 and quantitative theories capable of predicting such crowd dynamics,5,10−12 are rare. Here we show that simulations based on a model of pedestrian behaviour can provide valuable insights into the mechanisms of and preconditions for panic and jamming by incoordination. Our results suggest practical ways of minimising the harmful consequences of such events……….

The simulation of crowds at very large events

Hubert Klu ̈pfel

Abstract

In this article, we show two examples for the application of pedestrian flow simulation and analysis: the World Youth Day 2005 (WYD) in Cologne and the (non-emergency) egress from a football stadium. Various circumstances are specific for religious events. The persons might perform rituals and therefore the patterns of movement or gathering are governed by rules that go beyond simple necessity or comfort. Furthermore, the persons are usually very much attracted by the (idealistic) aim of their pilgrimage. The final service at the WYD in Cologne, celebrated by the Pope, was the major event during the WYD. The paper is divided into three parts: The first section is concerned with the World Youth Day and the second with the egress from a football stadium. The final section summarizes the results, provides recommendations and concludes with the most important implications for the field of crowd dynamics simulation.

Understanding Human Behaviors in Crowds by Imitating the Decision-Making Process

Haosheng Zou, Hang Su, Shihong Song, Jun Zhu

Abstract

Crowd behavior understanding is crucial yet challenging across a wide range of applications, since crowd behavior is inherently determined by a sequential decision-making pro- cess based on various factors, such as the pedestrians’ own destinations, interaction with nearby pedestrians and antici- pation of upcoming events. In this paper, we propose a novel framework of Social-Aware Generative Adversarial Imita- tion Learning (SA-GAIL) to mimic the underlying decision- making process of pedestrians in crowds. Specifically, we in- fer the latent factors of human decision-making process in an unsupervised manner by extending the Generative Adversar- ial Imitation Learning framework to anticipate future paths of pedestrians. Different factors of human decision making are disentangled with mutual information maximization, with the process modeled by collision avoidance regularization and Social-Aware LSTMs. Experimental results demonstrate the potential of our framework in disentangling the latent decision-making factors of pedestrians and stronger abilities in predicting future trajectories.

Crowd Behavior Simulation with Emotional 

Contagion in Unexpected Multi-hazard Situations

Mingliang Xu, Xiaozheng Xie, Pei Lv, Jianwei Niu, Hua Wang Chaochao Li, Ruijie Zhu, Zhigang Deng and Bing Zhou

Abstract

Numerous research efforts have been conducted to simulate crowd movements, while relatively few of them are specifically focused on multi-hazard situations. In this paper, we propose a novel crowd simulation method by modeling the generation and contagion of panic emotion under multi-hazard circumstances. In order to depict the effect from hazards and other agents to crowd movement, we first classify hazards into different types (transient and persistent, concurrent and non- concurrent, static and dynamic) based on their inherent characteristics. Second, we introduce the concept of perilous field for each hazard and further transform the critical level of the field to its invoked-panic emotion. After that, we propose an emotional contagion model to simulate the evolving process of panic emotion caused by multiple hazards. Finally, we introduce an Emotional Reciprocal Velocity Obstacles (ERVO) model to simulate the crowd behaviors by augmenting the traditional RVO model with emotional contagion, which for the first time combines the emotional impact and local avoidance together. Our experiment results demonstrate that the overall approach is robust, can better generate realistic crowds and the panic emotion dynamics in a crowd. Furthermore, it is recommended that our method can be applied to various complex multi-hazard environments.

Exploring Determinants of Pre-movement Delays in a Virtual Crowd Evacuation Experiment

Nikolai W. F. Bode , Edward A. Codling

Abstract.

Understanding evacuations of high-occupancy buildings presents a major challenge in fire safety science. The total time individuals require to exit a building includes the time it takes them to respond to an alarm and decide to evacuate (pre- movement) and the time it takes them to walk along their chosen exit route (move- ment). Previous work has shown that variation in pre-movement times is responsible for substantial evacuation delays, but few controlled experiments on this have been conducted. Here, we present a virtual experiment that investigates the level of risk individuals take by collecting virtual objects before evacuating. We determine how over 1200 participants, who were recruited from visitors to the London Science Museum, respond to three factors: a reduction in their knowledge of a building, a change in the behaviour of other simulated evacuees and a change in how they are attached to the objects they can collect (potential gain versus loss). We confirm that collecting more objects is risky, as it affects evacuation success. In our experiment, 44.6% of participants choose extreme strategies by collecting either all or none of the available objects before evacuating. While the adoption of extreme strategies is affec- ted by all three factors we investigate, the only factor that significantly increases the average number of objects participants collect, regardless of extreme strategies, is loss aversion. Our work shows the potential of virtual experiments to safely, quickly and cheaply scope processes causing pre-movement time delays in crowd evacuations. This provides a starting point for further research.