Simulating crowd evacuation with socio-cultural, cognitive, and emotional elements

In this research, the effects of culture, cognitions, and emotions on crisis management and prevention are analysed. An agent-based crowd evacuation simulation model was created, named IMPACT, to study the evacuation process from a transport hub. To extend previous research, various socio-cultural, cognitive, and emotional factors were modelled, including: language, gender, familiarity with the environment, emotional contagion, prosocial behaviour, falls, group decision making, and compliance. The IMPACT model was validated against data from an evacuation drill using the existing EXODUS evacuation model. Results show that on all measures, the IMPACT model is within or close to the prescribed boundaries, thereby establishing its validity. Structured simulations with the validated model revealed important findings, including: the effect of doors as bottlenecks, social contagion speeding up evacuation time, falling behaviour not affecting evacuation time significantly, and travelling in groups being more beneficial for evacuation time than travelling alone. This research has important practical applications for crowd management professionals, including transport hub operators, first responders, and risk assessors

A multi-agent system approach in evaluating human spatio-temporal vulnerability to seismic risk using social attachment

International audienceSocial attachment theory states that individuals seek the proximity of attachment figures (e.g. family members, friends, colleagues, familiar places or objects) when faced with threat. During disasters, this means that family members may seek each other before evacuating, gather personal property before heading to familiar exits and places, or follow groups/crowds, etc. This hard-wired human tendency should be considered in the assessment of risk and the creation of disaster management plans. Doing so may result in more realistic evacuation procedures and may minimise the number of casualties and injuries. In this context, a dynamic spatio-temporal analysis of seismic risk is presented using SOLACE, a multi-agent model of pedestrian behaviour based on social attachment theory implemented using the Belief-Desire-Intention approach. The model focuses on the influence of human, social, physical and temporal factors on successful evacuation. Human factors considered include perception and mobility defined by age. Social factors are defined by attachment bonds, social groups, population distribution, and cultural norms. Physical factors refer to the location of the epicentre of the earthquake, spatial distribution/layout and attributes of environmental objects such as buildings, roads, barriers (cars), placement of safe areas, evacuation routes, and the resulting debris/damage from the earthquake. Experiments tested the influence of time of the day, presence of disabled persons and earthquake intensity. Initial results show that factors that influence arrivals in safe areas include (a) human factors (age, disability, speed), (b) pre-evacuation behaviours, (c) perception distance (social attachment, time of day), (d) social interaction during evacuation, and (e) physical and spatial aspects, such as limitations imposed by debris (damage), and the distance to safe areas. To validate the results, scenarios will be designed with stakeholders, who will also take part in the definition of a serious game. The recommendation of this research is that both social and physical aspects should be considered when defining vulnerability in the analysis of risk

Simulation model of pedestrian flow based on multi-agent system and Bayesian Nash equilibrium

Computer-based simulation is a means of exploring complex systems and has become the mainstream method of pedestrian research. In this research, a multi-agent simulation model of pedestrian flow will be established using a multi-agent system (MAS) and Bayesian Nash equilibrium. MAS is used to simulate the crowd movement and the interaction between pedestrians, and Bayesian Nash equilibrium is adopted to analyze the decision-making process of pedestrians. In contrast to previous pedestrian flow simulation modeling methods, this study adopts multi-agent modeling to realize the complete heterogeneity of pedestrians, so as to achieve more accurate simulation and make the research conclusions closer to reality. To be specific, we attempt to determine the cell side length and simulation time step of an initial model parameterized using a dataset of actual pedestrian movements. It allows more than one pedestrian to be in the same cell and stipulates that the utility of pedestrians decreases with the growing number of pedestrians in the cell. The Bayesian Nash equilibrium is applied to analyze the decision-making process of pedestrians and collision avoidance rules and interaction rules of agents are also formulated. A number of areas of further research are discussed

Studying the Impact of Trained Staff on Evacuation Scenarios by Agent-Based Simulation

Human evacuation experiments can trigger distress, be unethical and present high costs. As a solution, computer simulations can predict the effectiveness of new emergency management procedures. This paper applies multi-agent simulation to measure the influence of staff members with diverse training levels on evacuation time. A previously developed and validated model was extended with explicit mechanisms to simulate staff members helping people to egress. The majority of parameter settings have been based on empirical data acquired in earlier studies. Therefore, simulation results are expected to be realistic. Results show that staff are more effective in complex environments, especially when trained. Not only specialised security professionals but, especially, regular workers of shopping facilities and offices play a significant role in evacuation processes when adequately trained. These results can inform policy makers and crowd managers on new emergency management procedures

Group Affect in Complex Decision-Making: Theory and Formalisms from Psychology and Computer Science

Integrating affect in both individual and collective decision-making processes in order to solve real-world problems can be challenging. This research aims to: (1) investigate how group affect (moods, emotions, and feelings) can be integrated and formalized in the decision-making processes; (2) develop current practices; and (3) draw ideas for future perspectives and real-world applications. For this purpose, the role of affect in decision-making is investigated on the individual behavior level, emotional intelligence, and the collective behavior level. The used methodology consists of exploring and investigating the main characteristics developed in group affect in complex decision-making systems from psychology to computer science. From this, a common global structure is deduced: individual processes, group processes and emerging processes (bottom-up, top-down, and combination of bottom-up and top-down components). Following this, one psychological model and two computational models of group emotion and decision are analyzed, and discussed. Their different approaches to developing the main characteristics of a computational model integrating group affect in the decision-making process are highlighted. Finally, specific scenarios of real-world applications are presented in order to draw interesting and promising computational model perspectives

Ergonomists as designers: computational modelling and simulation of complex socio-technical systems

Contemporary ergonomics problems are increasing in scale, ambition, and complexity. Understanding and creating solutions for these multi-faceted, dynamic, and systemic problems challenges traditional methods. Computational modelling approaches can help address this methodological shortfall. We illustrate this potential by describing applications of computational modelling to: (1) teamworking within a multi-team engineering environment; (2) crowd behaviour in different transport terminals; and (3) performance of engineering supply chains. Our examples highlight the benefits and challenges for multi-disciplinary approaches to computational modelling, demonstrating the need for socio-technical design principles. Our experience highlights opportunities for ergonomists as designers and users of computational models, and the instrumental role that ergonomics can play in developing and enhancing complex socio-technical systems. Recognising the challenges inherent in designing computational models, we reflect on practical issues and lessons learned so that computational modelling and simulation can become a standard and valuable technique in the ergonomists’ toolkit

Reuniões de massas - Fenómenos e modelos de evacuação

Reuniões em massa, fazem parte do dia a dia e podem ocorrer em diferentes lugares, dependendo das especificidades do evento. Devido à baixa perceção de risco as pessoas tendem a subestimar a probabilidade de ocorrência de um desastre e as suas consequências negativas, no entanto a história mundial evidência que os tumultos nestas reuniões ocorrem frequentemente, sendo necessário estudar o comportamento da multidão. Este pressuposto permitiu desenvolver um trabalho de pesquisa através de revisão de literatura, analisando de forma abrangente os estudos existentes. A evacuação em larga escala é uma medida eficaz para mitigar o risco numa emergência, no entanto, sob a perspetiva da segurança apresenta um conjunto de desafios devido ao comportamento psicomotor do individuo interferir em todo o processo. Depois de décadas de modelos teóricos e onde a evacuação se limitava à análise prévia da arquitetura do espaço e ao número de sobreviventes, a simulação computacional tornou-se uma ferramenta padrão para planear e avaliar a evacuação de multidões, no entanto, muitos modelos são estruturalmente diferentes e poucos foram rigorosamente testados. A grande vantagem é a antevisão de diversos cenários, sem colocar em risco os indivíduos, verifica-se, no entanto, que reproduzir emoções, comportamentos experiências e conhecimentos é muito difícil.info:eu-repo/semantics/publishedVersio

A Collective Adaptive Approach to Decentralised k-Coverage in Multi-robot Systems

We focus on the online multi-object k-coverage problem (OMOkC), where mobile robots are required to sense a mobile target from k diverse points of view, coordinating themselves in a scalable and possibly decentralised way. There is active research on OMOkC, particularly in the design of decentralised algorithms for solving it. We propose a new take on the issue: Rather than classically developing new algorithms, we apply a macro-level paradigm, called aggregate computing, specifically designed to directly program the global behaviour of a whole ensemble of devices at once. To understand the potential of the application of aggregate computing to OMOkC, we extend the Alchemist simulator (supporting aggregate computing natively) with a novel toolchain component supporting the simulation of mobile robots. This way, we build a software engineering toolchain comprising language and simulation tooling for addressing OMOkC. Finally, we exercise our approach and related toolchain by introducing new algorithms for OMOkC; we show that they can be expressed concisely, reuse existing software components and perform better than the current state-of-the-art in terms of coverage over time and number of objects covered overall