skip to main content

Title: Effect of Peer Influence and Looting Concerns on Evacuation Behavior During Natural Disasters
We study evacuation dynamics in a major urban region (Mi- ami, FL) using a combination of a realistic population and social contact network, and an agent-based model of evacuation behavior that takes into account peer influence and concerns of looting. These factors have been shown to be important in prior work, and have been modeled as a threshold-based network dynamical systems model (2mode-threshold), which involves two threshold parameters - for a family's decision to evacuate and to remain in place for looting and crime concerns - based on the fraction of neighbors who have evacuated. The dynamics of such models are not well understood, and we observe that the threshold parameters have a signifi cant impact on the evacuation dynamics. We also observe counter-intuitive eff ects of increasing the evacuation threshold on the evacuated fraction in some regimes of the model parameter space, which suggests that the details of realistic networks matter in designing policies.
Authors:
; ; ; ; ; ;
Award ID(s):
1916805 1745207
Publication Date:
NSF-PAR ID:
10300636
Journal Name:
Complex Networks and their Applications
Sponsoring Org:
National Science Foundation
More Like this
  1. We study evacuation dynamics in a major urban region (Miami, FL) using a combination of a realistic population and social contact network, and an agent-based model of evacuation behavior that takes into account peer influence and concerns of looting. These factors have been shown to be important in prior work, and have been modeled as a threshold-based network dynamical systems model (2mode-threshold), which involves two threshold parameters|for a family's decision to evacuate and to remain in place for looting and crime concerns|based on the fraction of neighbors who have evacuated. The dynamics of such models are not well understood, andmore »we observe that the threshold parameters have a significant impact on the evacuation dynamics. We also observe counter-intuitive effects of increasing the evacuation threshold on the evacuated fraction in some regimes of the model parameter space, which suggests that the details of realistic networks matter in designing policies.« less
  2. Neighborhood e ects have an important role in evacuation decision-making by a family. Owing to peer influence, neighbors evacuating can motivate a family to evacuate. Paradoxically, if a lot of neighbors evacuate, then the likelihood of an individual or family deciding to evacuate decreases, for fear of crime and looting. Such behavior cannot be captured using standard models of contagion spread on networks, e.g., threshold, independent cascade, and linear threshold models. Here, we propose a new threshold-based graph dynamical system model, 2mode-threshold, which captures this dichotomy. We study theoretically the dynamical properties of 2mode-threshold in di fferent networks, and fimore »nd signi ficant diff erences from a standard threshold model. We build and characterize small world networks of Virginia Beach, VA, where nodes are geolocated families (households) in the city and edges are interactions between pairs of families. We demonstrate the utility of our behavioral model through agent-based simulations on these small world networks. We use it to understand evacuation rates in this region, and to evaluate the e ffects of modeling parameters on evacuation decision dynamics. Speci fically, we quantify the effects of (i) network generation parameters, (ii) stochasticity in the social network generation process, (iii) model types (2mode-threshold vs. stan- dard threshold models), (iv) 2mode-threshold model parameters, (v) and initial conditions, on computed evacuation rates and their variability. An illustrative example result shows that the absence of looting e ect can overpredict evacuation rates by as much as 50%.« less
  3. Timely evacuation is a standard recommendation by local agencies before disaster events such as hurricanes, which have enough advance notice. However, it has been observed in many recent disasters (e.g., Sandy), that only a small fraction of the population evacuates in time. Recent work by social scientists has examined the factors that influence household evacuation decisions; in addition to individual factors it has been found that peer effect plays a role in this decision but in two opposing ways. Specifically, households are motivated to evacuate if their neighbors evacuate. However, if too many neighbors leave then some households have concernsmore »of looting and crime, and they choose not to evacuate. This makes the dynamics of evacuation very complex. In this paper, we use a detailed agent based model to study the dynamics of evacuation in Virginia‚Äôs coastal region. We use data from a large survey and social contagion and collective action theories to develop the model. We evaluate different strategies to increase evacuation.« less
  4. Recent results from social science have indicated that neighborhood effects have an important role in an evacuation decision by a family. Neighbors evacuating can motivate a family to evacuate. On the other hand, if a lot of neighbors evacuate, then the likelihood of an individual or family deciding to evacuate decreases, for fear of looting. Such behavior cannot be captured using standard models of contagion spread on networks, e.g., threshold models. Here, we propose a new graph dynamical system model, 2mode-threshold, which captures such behaviors. We study the dynamical properties of 2mode-threshold in different networks, and find significant differences frommore »a standard threshold model. We demonstrate the utility of our model through agent based simulations on small world networks of Virginia Beach, VA. We use it to understand evacuation rates in this region, and to evaluate the effects of the model and of different initial conditions on evacuation decision dynamics.« less
  5. Chen, J.Y.C. (Ed.)
    In recent years there has been a sharp increase in active shooter events, but there has been no introduction of new technology or tactics capable of increasing preparedness and training for active shooter events. This has raised a major concern about the lack of tools that would allow robust predictions of realistic human movements and the lack of understanding about the interaction in designated simulation environments. It is impractical to carry out live experiments where thousands of people are evacuated from buildings designed for every possible emergency condition. There has been progress in understanding human movement, human motion synthesis, crowdmore »dynamics, indoor environments, and their relationships with active shooter events, but challenges remain. This paper presents a virtual reality (VR) experimental setup for conducting virtual evacuation drills in response to extreme events and demonstrates the behavior of agents during an active shooter environment. The behavior of agents is implemented using behavior trees in the Unity gaming engine. The VR experimental setup can simulate human behavior during an active shooter event in a campus setting. A presence questionnaire (PQ) was used in the user study to evaluate the effectiveness and engagement of our active shooter environment. The results show that majority of users agreed that the sense of presence was increased when using the emergency response training environment for a building evacuation environment.« less