Erika Frydenlund

Conceptualizing intragroup and intergroup dynamics within a controlled crowd evacuation

Social dynamics play a critical role in successful pedestrian evacuations. Crowd modeling research has made progress in capturing the way individual and group dynamics affect evacuations; however, few studies have simultaneously examined how individuals and groups interact with one another during egress. To address this gap, the researchers present a conceptual agent-based model (ABM) designed to study the ways in which autonomous, heterogeneous, decision-making individuals negotiate intragroup and intergroup behavior while exiting a large venue. A key feature of this proposed model is the examination of the dynamics among and between various groupings, where heterogeneity at the individual level dynamically affects group behavior and subsequently group/group interactions. ABM provides a means of representing the important social factors that affect decision making among diverse social groups. Expanding on the 2013 work of Vizzari et al., the researchers focus specifically on social factors and decision making at the individual/group and group/group levels to more realistically portray dynamic crowd systems during a pedestrian evacuation. By developing a model with individual, intragroup, and intergroup interactions, the ABM provides a more representative approximation of real-world crowd egress. The simulation will enable more informed planning by disaster managers, emergency planners, and other decision makers. This pedestrian behavioral concept is one piece of a larger simulation model. Future research will build toward an integrated model capturing decision-making interactions between pedestrians and vehicles that affect evacuation outcomes.

Generic Incident Model for Investigating Traffic Incident Impacts on Evacuation Times in Large-Scale Emergencies

Traffic incidents cause a ripple effect of reduced travel speeds, lane changes, and the pursuit of alternative routes that results in gridlock on the immediately affected and surrounding roadways. The disruptions caused by the secondary effects significantly degrade travel time reliability, which is of great concern to the emergency planners who manage evacuations. Outcomes forecast by a generic incident model embedded in a microscopic evacuation simulation, the Real-Time Evacuation Planning Model (RtePM), were examined to quantify the change in time required for an emergency evacuation that results from traffic incidents. The incident model considered vehicle miles traveled on each individual segment of the studied road network model. The two scenarios considered for this investigation were evacuations of (a) Washington, D.C., after a simulated terrorist attack and (b) Virginia Beach, Virginia, in response to a simulated hurricane. These results could help the emergency planning community understand and investigate the impact of traffic incidents during an evacuation.

Agent-based modeling and strategic group formation: a refugee case study

Refugee flight presents a logistics problem for humanitarian aid workers anticipating ebbs and flows of arrivals. These migrations include travel over long distances with little advanced coordination and damaged social networks. The model presented here is based on these two fundamental premises: long distance and strategic en-route coordination. Assuming that over large distances, refugees attempt to construct groups that provide assistance or security as they navigate toward safety, the agent-based model incorporates cooperative game theory to investigate the impact of group formations on egress times. The modeled refugees make decisions based on individual utility functions informed by two factors, speed of the group and group size. Since groups accommodate slower members, they may reform as refugees choose their best available strategies to reach safety. The results indicate a tipping point in average group size as the slowest group members have more of impact in the utility function of the agents.

Panic That Spreads Sociobehavioral Contagion in Pedestrian Evacuations

Crowds are a part of everyday public life, from stadiums and arenas to school hallways. Occasionally, pushing within the crowd spontaneously escalates to crushing behavior, resulting in injuries and even death. The rarity and unpredictability of these incidents provides few options to collect data for research on the prediction and prevention of hazardous emergent behaviors in crowds. This study takes a close look at the way states of agitation, such as panic, can spread through crowds. Group composition—mainly family groups composed of members with differing mobility levels—plays an important role in the spread of agitation through the crowd, ultimately affecting the exit density and evacuation clearance time of a simulated venue. This study used an agent-based model of pedestrian movement during the egress of a hypothetical room and adopted an emotional, cognitive, and social framework to explore the transference and dissipation of agitation through a crowd. The preliminary results reveal that average group size in a crowd is a primary contributor to the exit density and evacuation clearance time. The study provides the groundwork on which to build more elaborate models that incorporate sociobehavioral aspects to simulate human movement during panic situations and account for the potential for dangerous behavior to emerge in crowds.

Exploring a Toll Auction Mechanism Enabled by Vehicle-to-Infrastructure Technology

High-occupancy toll (HOT) lanes—an increasingly popular solution for congested roadway networks—give drivers the option to access express lanes. The cost of entry often varies with demand, although no standard method of optimizing these price points exists. Using the principles of a Vickrey auction that incentivizes true-value bids, this paper proposes a tolling system that uses vehicle-to-infrastructure technology to optimize toll operator revenue with HOT lane usage. In the scenario, a roadway network consists of a HOT lane and a general-purpose lane, each with identical physical properties. Drivers can access the HOT lane at the start of the facility or at one interim point along the roadway. With the use of a triangular distribution to approximate the distribution of travelers’ value of time (VOT), the model explores the impact of varying the distributions mode on revenue earned by the toll operator. Results from the model indicate that when the toll operator maximizes the models revenue, the percentage of auction bids accepted for toll road access is robust to changes in the VOT distribution. This percentage equates to approximately 17% of vehicles accessing the facility. Given the difficulty in obtaining actual travelers’ distribution of VOT, this auction tolling mechanism implies that obtaining an exact VOT distribution may not be necessary for this type of tolling analysis.

Model Co-creation from a Modeler’s Perspective: Lessons Learned from the Collaboration Between Ethnographers and Modelers

This paper reports on the authors’ ongoing collaboration on model co-creation, a process that involves not only the reconciliation of methodologies (qualitative vs. quantitative), but also of epistemologies (empirical vs empirical/rationalist) and ontologies (observable referent vs. abstracted referent). The co-creation process has taken place over several months, from early 2017, both in person, teleconferencing and via email. The result was an ethnographic model of the refugee situation in Lesbos, Greece. The qualifier “ethnographic” means that the simulation’s purpose was to capture the problem situation described by ethnographers in a manner that resembles their observations, not to answer a research question. Ethnographers used the modeling process – mostly elicitation and variable identification - to think about questions they had not considered in the field. Further, the used the prototype model to further narrow their desired modeling scope and ask new questions. Lastly, notes captured by the ethnographers in the field highlight the challenges of the modeling situation.

Modeling the Impact of Protraction on Refugee Identity

This study presents an agent-based model of identity shift based on refugees in protracted situations. The model is based on interactions between refugees, local citizens, and nongovernmental workers. Through repeated interactions at the individual level, we see the emergence of groups of identities that are generally neutral—not nationalistic nor specifically locally or globally focused. The model provides a starting point for understanding the processes of long-term protracted states of displacement on the general shift in identity among refugee populations in both camp and non-camp based settings.

Flipping Coins and Coding Turtles

Nearly four decades ago, Thomas Schelling used coins and a checkerboard to simulate how simple social rules could produce stark neighborhood segregation. That early social science model marked the beginning of a movement to incorporate simulation into social science that continues to gain momentum today. Using political science and international studies as a frame of reference, this chapter explores the incomplete permeation of simulation into the statistical and qualitative research toolkits of those pursuing social inquiry. We begin by chronicling the development of several key advancements in modeling social systems, including formal modeling such as game theory, the adoption of statistical and computer-based modeling, and the advancement of computational social sciences using evolutionary computation and other dynamic modeling paradigms. Then, we discuss how and why simulation remains at the periphery of social science research methodologies. We compare a classic Prisoner’s Dilemma model to one designed using an agent-based simulation approach to illustrate the population ecology of emergent strategies. The chapter concludes with a discussion on the ways simulation of social systems would have to evolve to have more impact on the field of social sciences.