Xiaoyan Zhang, Graham Coates, Sarah Dunn, & Jean Hall. (2020). Emergency Evacuation from a Multi-floor Building using Agent-based Modeling. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 188–199). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper presents an overview of the ongoing research into the development of an agent-based model to enable simulations to be performed of agents evacuating from a multi-floor building with a complex layout, including staircases. Specifically, a flow field of navigation objects is constructed pre-computation, which stores the directions and shortest distances to all exits and staircases. Using the flow field, a navigation method is proposed for agents familiar with the environment to identify and follow the shortest route to a chosen exit. Preliminary simulations have been performed to investigate the effect on evacuation time of (i) exit configurations and (ii) familiarity of agents with the building layout. In assessing the effect of exit configurations, results show that the location of the main entrance has a significant influence on evacuation time. In addition, having more exits does not necessarily lead to a shorter evacuation time. In terms of the effect of familiarity of agents, having more agents with a greater level of familiarity does not significantly reduce evacuation time in most cases.
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Xiaoyan Zhang, Graham Coates, & Xiaoyang Ni. (2017). Agent-based Modelling and Simulation for Lecture Theatre Emergency Evacuation. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 63–71). Albi, France: Iscram.
Abstract: This paper presents an overview of ongoing research into the implementation of an agent-based model aimed at providing decision support for the layout design of lecture theatres and human behavioural management in emergency evacuation. The model enables the spatial layout of lecture theatres to be configured and incorporates agent behaviours at the basic movement and individual level. In terms of individual behaviours, agents can be competitive, cooperative, climb obstacles (e.g. seating and desks) and fall down. Two cases are investigated to evaluate the effects of different exit locations in lecture theatres and competitive behaviour of agents on evacuation efficiency in multiple scenarios.
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Xiaoyong Ni, Hong Huang, Shiwei Zhou, Boni Su, Jianchun Zheng, Wei Zhu, et al. (2018). Simulation of The Urban Waterlogging and Emergency Response Strategy at Subway Station's Entry-exit Platform in Heavy Rainstorm. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 99–120). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Underground space like subway stations is prone to be flooded which can lead to severe and unpredictable damage and even threaten human lives. In this paper, four groups of contrastive simulation of urban waterlogging at two subway stations' entry-exit platforms in heavy rainstorm are conducted, and emergency response strategies are suggested. A waterlogging simulation method named UPFLOOD based on shallow water equations is proposed considering complex topography. It has been found that the waterlogging at subway station's entry-exit platforms is easily influenced by several factors and the site selection of the subway stations is very important. A disaster process construction method based on PN model is proposed and it has been found that the response strategies including plugging, drainage and evacuation are important for disaster mitigation. This study helps decision makers to response quickly to meet the emergency of the waterlogging disaster at subway stations caused by heavy rainstorm.
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Xiaoyong Ni, Hong Huang, Wenxuan Dong, Chao Chen, Boni Su, & Anying Chen. (2021). Scenario Prediction and Crisis Management for Rain-induced Waterlogging Based on High-precision Simulation. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 159–173). Blacksburg, VA (USA): Virginia Tech.
Abstract: Many cities, especially those in developing countries, are not well prepared for the devastating disaster of exceptional rain-induced waterlogging caused by extreme rainfall. This paper proposes a waterlogging scenario prediction and crisis management method for such kind of extreme rainfall conditions based on high-precision waterlogging simulation. A typical urban region in Beijing, China is selected as the study area in this paper. High-precision and full-scale data in the study area requested for the waterlogging simulation are introduced. The simulation results show that the study area is still vulnerable to extreme rainfall and the subsequent waterlogging. The waterlogging situation is much more severe with the increase of the return period of rainfall. This study offers a good reference for the relevant government departments to make effective policy and take pointed response to the waterlogging problem.
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Sarp Yeletaysi, Frank Fiedrich, & John R. Harrald. (2008). A framework for integrating GIS and systems simulation to analyze operational continuity of the petroleum supply chain. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 586–595). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Crisis and disaster management is a field that requires the understanding and application of tools and knowledge from multiple disciplines. Hurricanes Katrina and Rita in 2005 have proven that U.S. petroleum infrastructure is vulnerable to major supply disruptions as a direct result of disasters. Due to the structure of U.S. oil supply chain, primary oil production centers (i.e. PADD* 3) are geographically separated from primary demand centers (i.e. PADD 1), which creates a natural dependency between those districts. To better understand the extent of those dependencies and downstream impacts of supply disruptions, a multi-disciplinary research approach is necessary. The cross-disciplines in this research include disaster management, critical infrastructure and oil supply chain management, and the utilization of geographic information systems (GIS) and systems simulation. This paper specifically focuses on the framework for integrating GIS and systems simulation as analysis tools in this research.
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Shengcheng Yuan, Ma Ma, H. Zhang, & Yi Liu. (2013). An urban traffic evacuation model with decision-making capability. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 317–321). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Traffic evacuation is one of the most challenging problems in a mega city due to crowded road conditions. This study focuses on developing a traffic evacuation model with decision-making capability. The model basically consists of two modules. The first one is a decision-making support module which runs very fast and provides short-forecast. The second one is a simulation module, which is used for simulating real evacuation process and for overall performance evaluation with vehicle tracking model. The first module can be considered as a “local” module as only partial information, such as traffic information in certain junctions is available. The second module can be considered as a global module which provides traffic directions for junction, and effective using of road-nets. With integration of two modules, overall system optimization may be achieved. Simulation cases are given for model validation and results are satisfied.
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Shengcheng Yuan, Yi Liu, Gangqiao Wang, Hongshen Sun, & H. Zhang. (2014). A dynamic-data-driven driving variability modeling and simulation for emergency evacuation. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 70–74). University Park, PA: The Pennsylvania State University.
Abstract: This paper presents a dynamic data driven approach of describing driving variability in microscopic traffic simulations for both normal and emergency situations. A four-layer DGIT (Decision, Games, Individual and Transform) framework provides the capability of describing the driving variability among different scenarios, vehicles, time and models. A four-step CCAR (Capture, Calibration, Analysis and Refactor) procedure captures the driving behaviors from mass real-time data to calibrate and analyze the driving variability. Combining the DGIT framework and the CCAR procedure, the system can carry out adaptive simulation in both normal and emergency situations, so that be able to provide more accurate prediction of traffic scenarios and help for decision-making support. A preliminary experiment is performed on a major urban road, and the results verified the feasibility and capability of providing prediction and decision-making support.
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Yue Guan, Shifei Shen, & Hong Huang. (2015). Assessment of the radiation doses to the public from the cesium in oceans after Fukushima Nuclear Accident. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: A great number of radioactive cesium were released into sea water after Fukushima Accident. We modified the Regional Oceanic Modelling System (ROMS) to reproduce the dispersion process of the cesium in oceans. The simulated water concentration was in good agreement with observation. In order to explore the nuclear impact of these contaminant in ocean, we established a food web model to calculate the concentration in marine organisms and assess the internal dose rate to the public. The estimated internal dose rate is small compared with the recommended limit by International Atomic Energy Agency (IAEA). Then, we employed the Monte Carlo N Particle Transport Code (MCNP) to calculate the transfer coefficient. The external dose rate could be estimated by this coefficient and simulated water concentration.
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Telmo Zarraonandia, Victor A. Bañuls, Ignacio Aedo, Paloma Díaz, & Murray Turoff. (2014). A scenario-based virtual environment for supporting emergency training. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 597–601). University Park, PA: The Pennsylvania State University.
Abstract: Simulation exercises are particularly popular for training in emergency situations. Exercises can vary in their degree of realism, complexity and level of stress, but they all try to reproduce a scenario of a real emergency so that each participant simulates the actions carried out for the role they should play. They not only support effective and situated learning, but they can also serve to improve the plan by allowing the identification of weak points and potential drawbacks in it. To facilitate the design and implementation of 3D virtual environments in which training exercises can be conducted, in this paper we propose to use the Cross-Impact Analysis technique in combination with an educational game platform called GRE. We also present a Simulation Authoring Tool that allows the designer to carry out the integration of the knowledge captured by means of Cross-Impact into the game designs that GRE can interpret.
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Zeleskidis, A., Chalarampidou, S., Dokas, I. M., & Torra, F. (2023). COBOT Safety Awareness: A RealTSL Demonstration in a Simulated System. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 874–891). Omaha, USA: University of Nebraska at Omaha.
Abstract: This work aims to propose the RealTSL methodology to empower collaborative robotic systems with self-safety awareness capability and address the methodology's limitation in determining time ranges for the unsafe system state transitions, which are inputs of the methodology. The COBOT system used in this paper to demonstrate RealTSL is an automated scissor lift robot to be used by first responders for “work at height,” simulated in Simulink™. The demonstration begins by 1) applying STPA to the system, 2) applying Early Warning Sign Analysis based on STAMP (EWaSAP), 3) creating an acyclic diagram that depicts system state transitions towards unsafe states, 4) incorporating the appropriate sensory equipment in the simulation, 5) simulating the system's operation for different scenarios using fault injection and finally 6) use information from the simulations to complete the RealTSL analysis and calculate the safety level of the system in real-time during its simulated operation.
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Zeno Franco, Nina Zumel, John Holman, Kathy Blau, & Larry E. Beutler. (2009). Evaluating the impact of improvisation on the incident command system: A modified single case study using the DDD simulator. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This study attempted to evaluate the utility of the Incident Command System (ICS) in varying disaster contexts. ICS is mandated in the United States and practitioners assert that it is an effective organizing system for emergency management. However, researchers contend that the utility of ICS is conflated with inter-team familiarity gained during ICS exercises. A military team-in-the-loop simulator was customized to represent the problems, resources, and command structures found in civilian led disaster management teams. A modified single case design drawn from behavioral psychology was used to explore possible casual relationships between changes team heterogeneity and performance. The design also allowed for the evaluation of improvisation on performance. Further, psychological factors that may underpin improvisation were explored. In addition to some preliminary empirical findings, the successes and difficulties in adapting the DDD simulator are briefly discussed as part of an effort to achieved greater interdisciplinary integration.
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Christopher W. Zobel, Stanley E. Griffis, Steven A. Melnyk, & John R. MacDonald. (2012). Characterizing disaster resistance and recoveryusing outlier detection. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Most definitions of disaster resilience incorporate both the capacity to resist the initial impact of a disaster and the ability to recover after it occurs. Being able to characterize and analyze resilient behavior can lead to improved understanding not only of the capabilities of a given system, but also of the effectiveness of different strategies for improving its resiliency. This paper presents an approach for quantifying the transient behavior resulting from a disaster event in a way that allows researchers to not only describe the transient response but also assess the impact of various factors (both main and interaction effects) on this response. This new approach combines simulation modeling, time series analysis, and statistical outlier detection to differentiate between disaster resistance and disaster recovery. Following the introduction of the approach, the paper provides a preliminary look at its relationship to the existing concept of predicted disaster resilience. © 2012 ISCRAM.
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