The Cry Wolf Effect in Evacuation: a Game-Theoretic Approach

In today's terrorism-prone and security-focused world, evacuation emergencies, drills, and false alarms are becoming more and more common. Compliance to an evacuation order made by an authority in case of emergency can play a key role in the outcome of an emergency. In case an evacuee experiences repeated emergency scenarios which may be a false alarm (e.g., an evacuation drill, a false bomb threat, etc.) or an actual threat, the Aesop's cry wolf effect (repeated false alarms decrease order compliance) can severely affect his/her likelihood to evacuate. To analyse this key unsolved issue of evacuation research, a game-theoretic approach is proposed. Game theory is used to explore mutual best responses of an evacuee and an authority. In the proposed model the authority obtains a signal of whether there is a threat or not and decides whether to order an evacuation or not. The evacuee, after receiving an evacuation order, subsequently decides whether to stay or leave based on posterior beliefs that have been updated in response to the authority's action. Best-responses are derived and Sequential equilibrium and Perfect Bayesian Equilibrium are used as solution concepts (refining equilibria with the intuitive criterion). Model results highlight the benefits of announced evacuation drills and suggest that improving the accuracy of threat detection can prevent large inefficiencies associated with the cry wolf effect.Comment: To be published in Physica

Modeling Helping Behavior in Emergency Evacuations Using Volunteer's Dilemma Game

People often help others who are in trouble, especially in emergency evacuation situations. For instance, during the 2005 London bombings, it was reported that evacuees helped injured persons to escape the place of danger. In terms of game theory, it can be understood that such helping behavior provides a collective good while it is a costly behavior because the volunteers spend extra time to assist the injured persons in case of emergency evacuations. In order to study the collective effects of helping behavior in emergency evacuations, we have performed numerical simulations of helping behavior among evacuees in a room evacuation scenario. Our simulation model is based on the volunteer's dilemma game reflecting volunteering cost. The game theoretic model is coupled with a social force model to understand the relationship between the spatial and social dynamics of evacuation scenarios. By systematically changing the cost parameter of helping behavior, we observed different patterns of collective helping behaviors and these collective patterns are summarized with a phase diagram.Comment: International Conference on Computational Science (ICCS) 2020 Conference Pape

Role of opinion sharing on the emergency evacuation dynamics

Emergency evacuation is a critical research topic and any improvement to the existing evacuation models will help in improving the safety of the evacuees. Currently, there are evacuation models that have either an accurate movement model or a sophisticated decision model. Individuals in a crowd tend to share and propagate their opinion. This opinion sharing part is either implicitly modeled or entirely overlooked in most of the existing models. Thus, one of the overarching goal of this research is to the study the effect of opinion evolution through an evacuating crowd. First, the opinion evolution in a crowd was modeled mathematically. Next, the results from the analytical model were validated with a simulation model having a simple motion model. To improve the fidelity of the evacuation model, a more realistic movement and decision model were incorporated and the effect of opinion sharing on the evacuation dynamics was studied extensively. Further, individuals with strong inclination towards particular route were introduced and their effect on overall efficiency was studied. Current evacuation guidance algorithms focuses on efficient crowd evacuation. The method of guidance delivery is generally overlooked. This important gap in guidance delivery is addressed next. Additionally, a virtual reality based immersive experiment is designed to study factors affecting individuals\u27 decision making during emergency evacuation

CellEVAC: an adaptive guidance system for crowd evacuation through behavioral optimization

A critical aspect of crowds' evacuation processes is the dynamism of individual decision making. Identifying optimal strategies at an individual level may improve both evacuation time and safety, which is essential for developing efficient evacuation systems. Here, we investigate how to favor a coordinated group dynamic through optimal exit-choice instructions using behavioral strategy optimization. We propose and evaluate an adaptive guidance system (Cell-based Crowd Evacuation, CellEVAC) that dynamically allocates colors to cells in a cellbased pedestrian positioning infrastructure, to provide efficient exit-choice indications. The operational module of CellEVAC implements an optimized discrete-choice model that integrates the influential factors that would make evacuees adapt their exit choice. To optimize the model, we used a simulation?optimization modeling framework that integrates microscopic pedestrian simulation based on the classical Social Force Model. In the majority of studies, the objective has been to optimize evacuation time. In contrast, we paid particular attention to safety by using Pedestrian Fundamental Diagrams that model the dynamics of the exit gates. CellEVAC has been tested in a simulated real scenario (Madrid Arena) under different external pedestrian flow patterns that simulate complex pedestrian interactions. Results showed that CellEVAC outperforms evacuation processes in which the system is not used, with an exponential improvement as interactions become complex. We compared our system with an existing approach based on Cartesian Genetic Programming. Our system exhibited a better overall performance in terms of safety, evacuation time, and the number of revisions of exit-choice decisions. Further analyses also revealed that Cartesian Genetic Programming generates less natural pedestrian reactions and movements than CellEVAC. The fact that the decision logic module is built upon a behavioral model seems to favor a more natural and effective response. We also found that our proposal has a positive influence on evacuations even for a low compliance rate (40%).Ministerio de Economía y Competitivida

Uncertainty in a spatial evacuation model

Pedestrian movements in crowd motion can be perceived in terms of agents who basically exhibit patient or impatient behavior. We model crowd motion subject to exit congestion under uncertainty conditions in a continuous space and compare the proposed model via simulations with the classical social force model. During a typical emergency evacuation scenario, agents might not be able to perceive with certainty the strategies of opponents (other agents) owing to the dynamic changes entailed by the neighborhood of opponents. In such uncertain scenarios, agents will try to update their strategy based on their own rules or their intrinsic behavior. We study risk seeking, risk averse and risk neutral behaviors of such agents via certain game theory notions. We found that risk averse agents tend to achieve faster evacuation time whenever the time delay in conflicts appears to be longer. The results of our simulations also comply with previous work and conform to the fact that evacuation time of agents becomes shorter once mutual cooperation among agents is achieved. Although the impatient strategy appears to be the rational strategy that might lead to faster evacuation times, our study scientifically shows that the more the agents are impatient, the slower is the egress time

A Study on Human Evacuation Behavior Involving Individuals with Disabilities in a Building

The individuals with disabilities are disproportionately vulnerable to hazards. However, there is very little research inquiry focused on evacuation environments and the behavior of individuals with disabilities. The most widely applied computational method used to study how effective the built environment facilities emergency evacuations in individuals-based modeling. Current pedestrian evacuation models rarely include individuals with disabilities in their simulated populations due to there being very few empirical studies of the evacuation behavior of individuals with disabilities. As a result, the models do not replicate accurate patterns of pedestrian or evacuation behavior of a heterogeneous population, which results in the evacuation needs of individuals with disabilities being generally overlooked. To begin addressing this limitation, our research group at Utah State University (USU) has performed empirical research to observe the microscopic evacuation behavior of individuals with disabilities in heterogeneous population contexts. The purpose of this research was to: (1) develop and analyze evacuation curves to understand and assess evacuation strategies for heterogeneous populations, and (2) analyze the microscopic behavior of evacuees at exit doors necessary for developing credible and valid pedestrian and evacuation models. Doing so will contribute to evacuation models which replicate accurate patterns of pedestrian and evacuation behavior of heterogeneous populations, leading to the consideration of the evacuation needs of individuals with disabilities

Adaptive cell-based evacuation systems for leader-follower crowd evacuation

The challenge of controlling crowd movement at large events expands not only to the realm of emergency evacuations but also to improving non-critical conditions related to operational efficiency and comfort. In both cases, it becomes necessary to develop adaptive crowd motion control systems. In particular, adaptive cell-based crowd evacuation systems dynamically generate exit-choice recommendations favoring a coordinated group dynamic that improves safety and evacuation time. We investigate the viability of using this mechanism to develop a ‘‘leader-follower’’ evacuation system in which a trained evacuation staff guides evacuees safely to the exit gates. To validate the proposal, we use a simulation–optimization framework integrating microscopic simulation. Evacuees’ behavior has been modeled using a three-layered architecture that includes eligibility, exit-choice changing, and exit-choice models, calibrated with hypothetical-choice experiments. As a significant contribution of this work, the proposed behavior models capture the influence of leaders on evacuees, which is translated into exitchoice decisions and the adaptation of speed. This influence can be easily modulated to evaluate the evacuation efficiency under different evacuation scenarios and evacuees’ behavior profiles. When measuring the efficiency of the evacuation processes, particular attention has been paid to safety by using pedestrian Macroscopic Fundamental Diagrams (p-MFD), which model the crowd movement dynamics from a macroscopic perspective. The spatiotemporal view of the evacuation performance in the form of crowd-pressure vs. density values allowed us to evaluate and compare safety in different evacuation scenarios reasonably and consistently. Experimental results confirm the viability of using adaptive cell-based crowd evacuation systems as a guidance tool to be used by evacuation staff to guide evacuees. Interestingly, we found that evacuation staff motion speed plays a crucial role in balancing egress time and safety. Thus, it is expected that by instructing evacuation staff to move at a predefined speed, we can reach the desired balance between evacuation time, accident probability, and comfort

Serious Game for Fire Evacuation

Fire safety for buildings has been of increasing concern due to the increase in occupant density in modern-day infrastructures. Efforts have been made by civil engineers to reduce loss in building fire accidents. For example, building codes have been refined to reduce the potential damage caused by fire by enforcing installation of fire detectors, alarm system, ventilation system, and sprinkler system. In addition, current building codes regulate the number of exits as well as the widths and heights of exits to allow an efficient evacuation process if the fire goes out of control. However the fire evacuation training aspect of fire safety is relatively immature. The fire evacuation process is still trained by carrying out traditional fire drills. However, the value of traditional fire drills has been questioned. Traditional fire evacuation drills fail to present a realistic fire environment to the participants. Traditional fire drills fail to raise enough seriousness for the participants since in most cases participants are informed about the drills beforehand. The cost of conducting these traditional fire drills can also be very high. Motivated by the problems faced by traditional fire drills, this research explores a new approach to more effectively and economically train people regarding the fire evacuation process. The new approach is to use a video game to train people for fire evacuation. The whole idea of using games for training and educational purposes falls under the concept of Serious Gaming, which has shown auspicious results in fields of military training, medical training, pilot training, and so on. In the virtual game environment, the fire environment can be simulated and rendered to the players. Doing so can allow the players to experience a more realistic fire environment and hence better prepare them for what to do in response to fire accidents. By setting a proper rewarding system, the game can motivate the players to treat the training more seriously. Also, since the training is carried out in the form of a game, it is more engaging and less costly. Currently, the game has been developed to render smoke and control the movement of agents. In order to make the game environment more realistic, the smoke is simulated and rendered using fire dynamics, and the agent movement is controlled by appropriate pedestrian models. It is worth mentioning that pedestrian modeling is still a relatively immature field of science and this game also serves as a tool for collecting and analyzing data for pedestrian models