Route Guidance Map for Emergency Evacuation

An efficient process of emergency evacuation must be guided. In the event of an evacuation instruction, a significant amount of time is spent by evacuees looking for a place of relative safety or an exit. Due to the ensuing stress and confusion evacuees try to follow others, consequently, all the exits are not used effectively. Therefore, it is important to develop a route guidance map for the emergency. The focus of the map is to help both, the evacuees and the authorities to perform evacuation efficiently. This paper presents a route guidance map for pedestrians that aims an efficient evacuation in case of an emergency. An agent-based simulation framework is used for the simulation of various scenarios to prepare the guiding map. A real world case study of Sarojini Nagar, Delhi is presented to test the presented methodology. Eventually, several strategic recommendations are provided for improving safety of existing infrastructure

Invisible control of self-organizing agents leaving unknown environments

In this paper we are concerned with multiscale modeling, control, and simulation of self-organizing agents leaving an unknown area under limited visibility, with special emphasis on crowds. We first introduce a new microscopic model characterized by an exploration phase and an evacuation phase. The main ingredients of the model are an alignment term, accounting for the herding effect typical of uncertain behavior, and a random walk, accounting for the need to explore the environment under limited visibility. We consider both metrical and topological interactions. Moreover, a few special agents, the leaders, not recognized as such by the crowd, are "hidden" in the crowd with a special controlled dynamics. Next, relying on a Boltzmann approach, we derive a mesoscopic model for a continuum density of followers, coupled with a microscopic description for the leaders' dynamics. Finally, optimal control of the crowd is studied. It is assumed that leaders exploit the herding effect in order to steer the crowd towards the exits and reduce clogging. Locally-optimal behavior of leaders is computed. Numerical simulations show the efficiency of the optimization methods in both microscopic and mesoscopic settings. We also perform a real experiment with people to study the feasibility of the proposed bottom-up crowd control technique.Comment: in SIAM J. Appl. Math, 201

LED wristbands for cell-based crowd evacuation: an adaptive exit-choice guidance system architecture

Cell-based crowd evacuation systems provide adaptive or static exit-choice indications that favor a coordinated group dynamic, improving evacuation time and safety. While a great effort has been made to modeling its control logic by assuming an ideal communication and positioning infrastructure, the architectural dimension and the influence of pedestrian positioning uncertainty have been largely overlooked. In our previous research, a cell-based crowd evacuation system (CellEVAC) was proposed that dynamically allocates exit gates to pedestrians in a cell-based pedestrian positioning infrastructure. This system provides optimal exit-choice indications through color-based indications and a control logic module built upon an optimized discrete-choice model. Here, we investigate how location-aware technologies and wearable devices can be used for a realistic deployment of CellEVAC. We consider a simulated real evacuation scenario (Madrid Arena) and propose a system architecture for CellEVAC that includes: a controller node, a radio-controlled light-emitting diode (LED) wristband subsystem, and a cell-node network equipped with active Radio Frequency Identification (RFID) devices. These subsystems coordinate to provide control, display, and positioning capabilities. We quantitatively study the sensitivity of evacuation time and safety to uncertainty in the positioning system. Results showed that CellEVAC was operational within a limited range of positioning uncertainty. Further analyses revealed that reprogramming the control logic module through a simulation optimization process, simulating the positioning system's expected uncertainty level, improved the CellEVAC performance in scenarios with poor positioning systems.Ministerio de Economía, Industria y Competitivida

Reactive and Proactive Anomaly Detection in Crowd Management Using Hierarchical Temporal Memory

An effective crowd management system offers immediate reactive or proactive handling of potential hot spots, including overcrowded situations and suspicious movements, which mitigate or avoids severe incidents and fatalities. The crowd management domain generates spatial and temporal resolution that demands diverse sophisticated mechanisms to measure, extract and process the data to produce a meaningful abstraction. Crowd management includes modelling the movements of a crowd to project effective mechanisms that support quick emersion from a dangerous and fatal situation. Internet of Things (IoT) technologies, machine learning techniques and communication methods can be used to sense the crowd characteristic /density and offer early detection of such events or even better prediction of potential accidents to inform the management authorities. Different machine learning methods have been applied for crowd management; however, the rapid advancement in deep hierarchical models that learns from a continuous stream of data has not been fully investigated in this context. For example, Hierarchical Temporal Memory (HTM) has shown powerful capabilities for application domains that require online learning and modelling temporal information. This paper proposes a new HTM-based framework for anomaly detection in a crowd management system. The proposed framework offers two functions: (1) reactive detection of crowd anomalies and (2) proactive detection of anomalies by predicting potential anomalies before taking place. The empirical evaluation proves that HTM achieved 94.22%, which outperforms k-Nearest Neighbor Global Anomaly Score (kNN-GAS) by 18.12%, Independent Component Analysis-Local Outlier Probability (ICA-LoOP) by 18.17%, and Singular Value Decomposition Influence Outlier (SVD-IO) by 18.12%, in crowd multiple anomaly detection. Moreover, it demonstrates the ability of the proposed alerting framework in predicting potential crowd anomalies. For this purpose, a simulated crowd dataset was created using MassMotion crowd simulation tool

Simulating The Evacuation Of Students Attending Classes At The York University's Keele Campus

Since 1901, Canada has recorded over a thousand disasters (CDD, 2015). Ontario, a province possessing the highest number of incidents and evacuations, has adapted and learned from these experiences. The Emergency Movement and Civil Protection Act (1990) for example, legally obliged government organizations to maintain an emergency management program. Despite the measures set out by the government there were still a dominant paradigm of disaster, leading many to believe nothing could be done, when one occurs, or that they would not be affected one. Morris (2009) proved otherwise when it came to school shootings (a technological disaster). Morris illustrated awareness and preparedness in school led to resilient students who were less affected by the disasters. An important observation, as school disasters in particular have the ability to cause jarring impacts to a community. This Major Paper presents a simulation model that evacuates students attending classes at the York University Keele Campus. The agent-based model was constructed with data acquired from York University's Office of Institutional Planning & Analysis, York University?s Planning & Architectural Design branch of the Campus Services and Business Operation, and scientific journals. The model reproduces the number of registered students during the winter semester of 2014, from Monday to Sunday. This cycle stops, when a signal is given, informing of an evacuation. From this instance, students, proceeded through a series of steps before arriving to one of four predetermined evacuation zones. These steps included: 1) pre-movement 2) descend the corresponding multi-floored building and 3) travel at an assigned speed to the evacuation zone. Forty evacuation scenarios, ten for each evacuation zones, were generated at varying times of day, throughout the week. The gathered times were further analyzed with three variables: the student population, the number of buildings holding classes, and the percentage of buildings within the vicinity of an evacuation zone. The student population demonstrated a logarithmic relationship with time, where evacuation time became more consistent as the population sized increased. When it came to the analysis of the number of buildings holding classes, the greater number of buildings, meant the buildings were more spread out and resulted in similar evacuation time for all four evacuation zones. The last case examined the percentage of buildings within the vicinity of an evacuation zone, half of the evacuation zones possessed a linear relationship, where the greater percentages meant a shorter arrival time

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

The co-evolution of competition and parasitism in the resource-based view:a risk model of product counterfeiting

The primary concern in the resource-based view of the firm has been competition. For many firms, however, the relevant ecology includes parasites as well as competitors – notably product counterfeiters who parasitically exploit a firm’s reputational resource. This parasitic process both diminishes the reputational resource it exploits, and produces significant risk of harm as a by-product. This article extends the resource-based view, presenting an account of the mechanism by which competition and parasitism co-evolve and produce a distinctive form of resource erosion. It does so using a model which, because a firm’s reputational resource exists distributedly in the minds of mutually-influencing but not centrally-coordinated consumers, takes an agent-based approach. This model then naturally forms a basis for the probabilistic risk assessment of the consequences of parasitism – particularly the harm that arises from the counterfeiting of safety critical products such as pharmaceuticals. The intended contribution is to show how the resource-based view can be extended to reflect the fact that heterogeneous resource distribution is implicated in parasitism as much as competition, and to show how a model of the underlying mechanisms can support risk analysis

Modeling Framework for Optimal Evacuation of Large-Scale Crowded Pedestrian Facilities

The paper presents a simulation–optimization modeling framework for the evacuation of large-scale pedestrian facilities with multiple exit gates. The framework integrates a genetic algorithm (GA) and a microscopic pedestrian simulation–assignment model. The GA searches for the optimal evacuation plan, while the simulation model guides the search through evaluating the quality of the generated evacuation plans. Evacuees are assumed to receive evacuation instructions in terms of the optimal exit gates and evacuation start times. The framework is applied to develop an optimal evacuation plan for a hypothetical crowded exhibition hall. The obtained results show that the model converges to a superior optimal evacuation plan within an acceptable number of iterations. In addition, the obtained evacuation plan outperforms conventional plans that implement nearest-gate immediate evacuation strategies

Simulating the Evacuation of Students Attending Classes at the York University’s Keele Campus

Since 1901, Canada has recorded over a thousand disasters (CDD, 2015). Ontario, a province possessing the highest number of incidents and evacuations, has adapted and learned from these experiences. The Emergency Movement and Civil Protection Act (1990) for example, legally obliged government organizations to maintain an emergency management program. Despite the measures set out by the government there were still a dominant paradigm of disaster, leading many to believe nothing could be done, when one occurs, or that they would not be affected one. Morris (2009) proved otherwise when it came to school shootings (a technological disaster). Morris illustrated awareness and preparedness in school led to resilient students who were less affected by the disasters. An important observation, as school disasters in particular have the ability to cause jarring impacts to a community. This Major Paper presents a simulation model that evacuates students attending classes at the York University Keele Campus. The agent-based model was constructed with data acquired from York University’s Office of Institutional Planning & Analysis, York University’s Planning & Architectural Design branch of the Campus Services and Business Operation, and scientific journals. The model reproduces the number of registered students during the winter semester of 2014, from Monday to Sunday. This cycle stops, when a signal is given, informing of an evacuation. From this instance, students, proceeded through a series of steps before arriving to one of four predetermined evacuation zones. These steps included: 1) pre-movement 2) descend the corresponding multi-floored building and 3) travel at an assigned speed to the evacuation zone. Forty evacuation scenarios, ten for each evacuation zones, were generated at varying times of day, throughout the week. The gathered times were further analyzed with three variables: the student population, the number of buildings holding classes, and the percentage of buildings within the vicinity of an evacuation zone. The student population demonstrated a logarithmic relationship with time, where evacuation time became more consistent as the population sized increased. When it came to the analysis of the number of buildings holding classes, the greater number of buildings, meant the buildings were more spread out and resulted in similar evacuation time for all four evacuation zones. The last case examined the percentage of buildings within the vicinity of an evacuation zone, half of the evacuation zones possessed a linear relationship, where the greater percentages meant a shorter arrival time