Key challenges in agent-based modelling for geo-spatial simulation

Agent-based modelling (ABM) is fast becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and space, generates emergent order, often at higher levels than those at which such agents operate. ABM however raises as many challenges as it seeks to resolve. It is the purpose of this paper to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems. The seven challenges we pose involve: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the ways the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. Once catalogued, we then illustrate these challenges with a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation tuned to London data which elaborates the standard Schelling (1971) model, and an agent-based residential location built according to spatial interactions principles, calibrated to trip data for Greater London. The ambiguities posed by this new style of modelling are drawn out as conclusions

Integrating a Human Behavior Model within an Agent-Based Approach for Blasting Evacuation

Several studies on Emergency Management are available in the literature, but most of them do not consider how the human behavior during an emergency can affect the evacuation process. Therefore, the novel contribution of this article is the implementation of an agent‐based model to describe the evacuation, due to a blast in a public area, integrated with a human behavior analytical model. Each agent has its own behavior that is described in a layered framework. The first layer simulates the “agent's features” function. Then, an “individual module” describes dynamically the emotional aspects using (i) the Decision Field Theory, (ii) a stationary stochastic model, and (iii) the results coming from a questionnaire. An agent‐based model with integrated human behavior is proposed to test critical infrastructures in emergency conditions without performing full scale evacuation tests. Analyses could be performed both in real time with a hazard scenario and at the design level to predict the system response to identify the optimal configuration. Therefore, the development of the proposed methodology could support both designers and policy makers in the decision‐making process

Optimising Pedestrian Flow Around Large Stadiums

This study proposes a method that combines the cellular automaton model and the differential evolution algorithm for optimising pedestrian flow around large stadiums. A miniature version of a large stadium and its surrounding areas is constructed via the cellular automaton model. Special mechanisms are applied to influence the behaviour of an agent that leaves from a certain stadium gate. The agent may be attracted to a nearby business facility and/or guided to uncongested areas. The differential evolution algorithm is then used to determine the optimal probabilities of the influencing agents for each stadium gate. The main goal is to reduce the evacuation time, and other goals such as reducing the costs for the influencing agents’ behaviours and the individual evacuation time are also considered. We found that, although they worked differently in different scenarios, the attraction and guidance of agents significantly reduced the evacuation time. The optimal evacuation time was achieved with moderate attraction to the business facilities and strong guidance to the detouring route. The results demonstrate that the proposed method can provide a goal-dependent, exit-specific strategy that is otherwise hard to acquire for optimising pedestrian flow

Agent-based models of social behaviour and communication in evacuations:A systematic review

Most modern agent-based evacuation models involve interactions between evacuees. However, the assumed reasons for interactions and portrayal of them may be overly simple. Research from social psychology suggests that people interact and communicate with one another when evacuating and evacuee response is impacted by the way information is communicated. Thus, we conducted a systematic review of agent-based evacuation models to identify 1) how social interactions and communication approaches between agents are simulated, and 2) what key variables related to evacuation are addressed in these models. We searched Web of Science and ScienceDirect to identify articles that simulated information exchange between agents during evacuations, and social behaviour during evacuations. From the final 70 included articles, we categorised eight types of social interaction that increased in social complexity from collision avoidance to social influence based on strength of social connections with other agents. In the 17 models which simulated communication, we categorised four ways that agents communicate information: spatially through information trails or radii around agents, via social networks and via external communication. Finally, the variables either manipulated or measured in the models were categorised into the following groups: environmental condition, personal attributes of the agents, procedure, and source of information. We discuss promising directions for agent-based evacuation models to capture the effects of communication and group dynamics on evacuee behaviour. Moreover, we demonstrate how communication and group dynamics may impact the variables commonly used in agent-based evacuation models

Agent-based models of social behaviour and communication in evacuations: A systematic review

Most modern agent-based evacuation models involve interactions between evacuees. However, the assumed reasons for interactions and portrayal of them may be overly simple. Research from social psychology suggests that people interact and communicate with one another when evacuating and evacuee response is impacted by the way information is communicated. Thus, we conducted a systematic review of agent-based evacuation models to identify 1) how social interactions and communication approaches between agents are simulated, and 2) what key variables related to evacuation are addressed in these models. We searched Web of Science and ScienceDirect to identify articles that simulated information exchange between agents during evacuations, and social behaviour during evacuations. From the final 70 included articles, we categorised eight types of social interaction that increased in social complexity from collision avoidance to social influence based on strength of social connections with other agents. In the 17 models which simulated communication, we categorised four ways that agents communicate information: spatially through information trails or radii around agents, via social networks and via external communication. Finally, the variables either manipulated or measured in the models were categorised into the following groups: environmental condition, personal attributes of the agents, procedure, and source of information. We discuss promising directions for agent-based evacuation models to capture the effects of communication and group dynamics on evacuee behaviour. Moreover, we demonstrate how communication and group dynamics may impact the variables commonly used in agent-based evacuation models.Comment: Pre-print submitted to Safety Science special issue following the 2023 Pedestrian and Evacuation Dynamics conferenc

Non-local first-order modelling of crowd dynamics: a multidimensional framework with applications

In this work a physical modelling framework is presented, describing the intelligent, non-local, and anisotropic behaviour of pedestrians. Its phenomenological basics and constitutive elements are detailed, and a qualitative analysis is provided. Within this common framework, two first-order mathematical models, along with related numerical solution techniques, are derived. The models are oriented to specific real world applications: a one-dimensional model of crowd-structure interaction in footbridges and a two-dimensional model of pedestrian flow in an underground station with several obstacles and exits. The noticeable heterogeneity of the applications demonstrates the significance of the physical framework and its versatility in addressing different engineering problems. The results of the simulations point out the key role played by the physiological and psychological features of human perception on the overall crowd dynamics.Comment: 26 pages, 17 figure

Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

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