Publish/Subscribe System Based on Event Calculus to Support Real-Time Multi-Agent Evacuation Simulation

In creating an evacuation simulation for training and planning, realistic agents that reproduce known phenomenon are required. Evacuation simulation in the airport domain requires additional features beyond most simulations, including the unique behaviors of first-time visitors who have incomplete knowledge of the area and families that do not necessarily adhere to often-assumed pedestrian behaviors. Evacuation simulations not customized for the airport domain do not incorporate the factors important to it, leading to inaccuracies when applied to it.In this paper, we describe ESCAPES, a multiagent evacuation simulation tool that incorporates four key features: (i) different agent types; (ii) emotional interactions; (iii) informational interactions; (iv) behavioral interactions. Our simulator reproduces phenomena observed in existing studies on evacuation scenarios and the features we incorporate substantially impact escape time. We use ESCAPES to model the International Terminal at Los Angeles International Airport (LAX) and receive high praise from security officials.

In a fire, stairways are the primary avenues for building evacuation. Previous studies focused on investigating evacuation flow through evacuation drills in a high-rise office building to assess the accuracy of evacuation scenarios and compared them with evacuation dynamics. However, the effectiveness of evacuation drills in estimating many scenarios is limited by actual drills. The evacuation simulations present a promising approach to objectively evaluating evacuation scenarios. This study verifies whether evacuation simulations can faithfully replicate actual evacuation flow and effectively predict suitable evacuation scenarios or potentially involve parameter calibration. Through a comprehensive comparison analysis, this study scrutinized the reliability of evacuation simulations and calibrated the simulation parameters. The analysis revealed that factors, including adjustments to the door width, personal space considerations for occupants in both conflict and normal situations and variations in staircase structure configuration, can significantly influence the evacuation flow within staircases. Manipulating these parameters in simulations would enable a more precise replication of evacuation flow within staircases, thereby enhancing the simulation’s accuracy in target evacuation scenarios. The findings of this research have underscored the significance of employing advanced simulation techniques to model evacuation dynamics accurately, facilitating a robust framework for devising effective emergency evacuation strategies in high-rise office buildings.

An agent-based modeling approach to collaborative classrooms evacuation process

In this paper, an evacuation simulation method is presented, which is embedded in a CFD based fire modelling programme. The evacuation programme allows the modelling of high crowd density situations and the interaction between evacuation simulations and state-of-the-art fire simulations. The evacuation process is modelled as a quasi-2D system, where autonomous agents simulating the escaping humans are moving according to equations of motion and decision making processes. The space and time, where the agents are moving, is taken to be continuous, but the building geometry is discretized using fine meshes. The model follows each agent individually and each agent has its own personal properties, like mass, walking velocity, familiar doors, etc. The fire and evacuation calculations interact via the smoke and gas concentrations. A reaction function model is used to select the exit routes. The model is compared to other evacuation simulation models using some test simulations.

Evacuation simulations are among essential analysis to assess the level of life safety in buildings. Currently, a number of evacuation modeling tools are available, each with unique characteristics. But, complexity of human behaviors made most of these tools ignore behavioral data in their models; and among those models which account for human behaviors, rule based modeling and rational decision making approaches are used for decision process. However, to achieve more realistic evacuation calculations, human-like decision making should be integrated to evacuation simulations. In this research we present a novel approach to build multi-agent evacuation simulations that exhibit more realistic simulation behaviors. We propose a model that integrates individual differences, such as personality, age, and gender, with naturalistic decision making, where human decision making in natural environments is investigated. The resulted decision process is applied to BDI agent architecture within a building evacuation system.KeywordsPersonality TraitEvacuation TimingPreference WeightingEmergency EvacuationNaturalistic DecisionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Recently, studies on evacuation simulations have drawn up scenarios of evacuation under various situations. In this study, a system is proposed to show the results of evacuation simulations for disasters such as tsunamis and fires, with maps and serial images taken by MMS (Mobile Mapping System). The all-around view camera, angle meter, and GPS (Global Positioning System) antenna are mounted on a moving object, such as a car, in MMS. The serially-taken images can be related to GIS (Geographic Information System). Users can not only virtually experience the evacuation but also find the dangerous places by observing the 360-degree surrounding image.

Integrating sensor networks in cloud computing gives new opportunities of using as many cloud-compute nodes as necessary to analyze real-time sensor data on the fly. However, most cloud services for parallelization such as OpenMP, MPI, and MapReduce are not always fitted to on-the-fly sensor-data analyses that are implemented as model-based entity-based, and multi-agent simulations. To address this semantic gap between analyzing algorithms and their actual implementations, we are developing MASS: a library for multi-agent spatial simulation that composes a user application of distributed array elements and multi-agents, each representing an individual simulation place or an active entity. All computation is enclosed in each of elements and agents that are automatically distributed over different computing nodes. Their communication is then scheduled as periodical data exchanges among those entities using their logical indices. We are currently implementing a multi-process and a multi-threaded version of the MASS library, both to be combined in a single version in the near future. This paper focuses on an implementation and preliminary performance of the multi-process version.

Effectiveness of the policy for organising self-evacuation by private vehicle transport, as verified in microsimulations

Building useful and efficient models and tools for a varied audience, such as evacuation simulators for scientists, engineers and crisis managers, can be tricky. Even good models can fail in providing information when the user’s tools for the model are scarce of resources. The aim of this work is to propose a new tool that covers the most required features in evacuation scenarios. This paper starts with a review of current software, prototypes and models simulating evacuation scenarios, by discussing their required and desired features. Based on this overview, we propose our simulator comparing it with other models and commercial tools. Moreover, we discuss the importance of building simulators that cover the minimum requirements to avoid the risk of building inefficient models or tools that do not provide enough insights for users to take right decisions in terms of security policies in crowded events. The implications of this work are to present a new simulation tool and to start a discussion in this research field on mandatory features of evacuation simulation tools that will provide valuable information to users and to find out what the criteria are to define these features.

During the evacuation process in an emergency, the route conditions usually change instantaneously, which makes routing selection a challenging work. To describe dynamic changes in the evacuation environment, this work proposes a real-time evacuation strategy based on a comprehensive route constraint in the framework of a cell-inspired simulation model, intelligence decision P system (IDPS). In our model, the comprehensive route constraint is formed to describe more complex road condition information including the total distance, congestion state, and unreliability of the route. Meanwhile, the IDPS model has been further improved in both the knowledge base description and the decision-making ability. Experiments are conducted to simulate five different scenarios in a fire evacuation. The results show that the evacuation strategy with a comprehensive route constraint has a significant improvement in the evacuation efficiency and has higher robustness. Which kind of route condition should be emphasized more in different evacuation scenarios is also analyzed.

Multi-agent Simulation of Passenger Evacuation from a Damaged Ship under Storm Conditions

Ship evacuation simulations have been used for years to track passengers during an emergency situation. However, current models are still relatively complex to use and are therefore only operated by ship designers at best and rarely by crew members in real situations. The goal of this research is to propose an interactive approach that would be used by crew members on board to organize evacuation drills and be able to interact in real time with the simulation. The approach combines an agent-based model, Python developments and the multi-agent-based Mesa library. Several scenarios of evacuation were tested as well as several pathfinding algorithms. A two-dimensional interface allows different interactive design options such as operating in a given deck, testing different passenger and overload situations. Simulation experiments show promising results as the system developed favors the observation of different evacuation behaviors and outputs as well as highlighting different structural and behavioral patterns in a ship indoor environment.

Multi-agent simulations (MAS) have been used to study the dynamics of social systems. Disaster-related simulation is one of application fields. The simulation is applied to scenarios that are difficult to perform drills in the real world. The results provide useful data such as the amount of time people take to evacuate buildings and how smoothly rescue responders arrive at target points in the buildings. Making use of the simulation results to plan disaster-prevention measure, we need to verify that the simulation results that are reasonable at scenarios that are not confirmed from real data and observations. In this paper, we discuss the standardization process of MAS-based evacuation simulations by examining qualitative differences perceived in our evacuation simulations.

Pedestrian evacuation risk of subway stations is an important concern in city management, as it not only endangers public safety but also affects the efficiency of urban subway transportation. Determination of how to effectively evaluate the pedestrian evacuation risk of subway stations is of great significance to improve pedestrian safety. Previous studies about the pedestrian evacuation of subway station were primarily focused on pedestrian moving behaviors and the evacuation modeling, and the evacuation scenario is the regular subway operation. There is a dearth of studies to quantify the pedestrian evacuation risk in the evacuation process, especially the pedestrian evacuation risk quantitative characterization of subway station in large-scale sport activity. The current study develops a quantitative pedestrian evacuation risk assessment model that integrates pedestrian stampede probability and pedestrian casualty. Then several different simulation scenarios based on the social force model (SFM) are simulated to evaluate the pedestrian evacuation risk of the “Olympic Park Station” in Beijing, China. The results demonstrate that the pedestrian evacuation method, pedestrian stampede location, and distance from the stampede location to the ticket gate have a large impact on pedestrian evacuation risk. Then, the pedestrian evacuation scenarios with the lowest and highest risk for the “Olympic Park Station” in large-scale sport activity are determined. The findings have potential applications in pedestrian safety protection of subway station during large-scale sports activity.

In 2004 at least 230,000 people were victims of the Aceh tsunami disaster. To prevent the recurrence of many victims, the Aceh government held an evacuation exercise in 2008. To improve effectiveness dan reduce the cost reduction during evacuations drills, simulation is the best option. Agent-Based Modeling is a simulation program that was employed for tsunami evacuation in Aceh. This study on tsunami evacuation using agent-based modelling presented and evaluated the different control parameters that affect the evacuation rate. Evacuation scenario during day or night has different environmental, agent base, road modelling, and population approach. The Road Network Model has explained that to analyze the effect of agents in the evacuation process, resident agents are presumed to know the direction and shortest path to the nearest evacuation points. This simulation designed in Netlogo is also able to assess the congestion possibility on the road network. The road network emphasized the different scenarios to discover the possibility of congestion points. Nighttime is proven to be the best scenario for performing the evacuation in the simulation. The key reason to select the night scenario is to maximize the effects of an evaluation of the road network. In addition, simulation using night scenarios is also expected to raise people’s awareness.