Yoshiki Ogawa, Yuki Akiyama, & Ryosuke Shibasaki. (2017). Extraction of significant scenarios for earthquake damage estimation using sparse modeling. 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. 150–163). Albi, France: Iscram.
Abstract: The recent diversification and accumulation of data from GPS equipped mobile phones, building sensors, and other resources in Japan has caused a large increase in the number of earthquake disaster scenarios that can be identified. Disaster prevention planning requires us to contemplate which scenario should be focused on and the required response to various scenarios. As a means to solve this problem, the damage distribution of building collapse and fire from GPS data can be used to estimate future damage based on people flow and various hypocenter models of earthquakes. We propose a method that uses sparse modeling to extract scenarios that are important for disaster estimation and prevention. As a result, this paper makes it possible to quickly grasp the scenario distribution, which was previously impossible to do, and to extract the significant scenarios.
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Yi Xiong, Weiping Si, & Xia Wu. (2016). Analysis of Emergency Response for Accident of Oil and Gas Pipeline Based on Stochastic Petri Net. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Emergency response plays an important role in reducing the loss of an accident. And the excellent plan is important to ensure the high efficiency of the emergency response system. However, actions of emergency response arranged in emergency plan can hardly be assessed before the plan is used. Stochastic Petri Net (SPN) is proposed to analyze the performance of emergency response for oil and gas pipeline accident. The results show that the average execution time of SPN model can be used to evaluate effectiveness of emergency response. Then place average mark number indicates that emergency decision-making is the most important segment to optimize emergency work flow. And utilization rate of transition shows that decreasing the cost time of maintenance is the key to improve efficiency of emergency response.
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Yan Wang, & John E. Taylor. (2017). Tracking urban resilience to disasters: a mobility network-based approach. 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. 97–109). Albi, France: Iscram.
Abstract: Disaster resilience is gaining increasing attention from both industry and academia, but difficulties in operationalizing the concept remain, especially in the urban context. Currently, there is scant literature on measuring both spatial and temporal aspects of resilience empirically. We propose a bio-inspired quantitative framework to track urban resilience to disasters. This framework was built upon a daily human mobility network, which was generated by geolocations from a Twitter Streaming API. System-wide metrics were computed over time (i.e. pre-, during and post-disasters). Fisher information was further adopted to detect the perturbation and dynamics in the system. Specifically, we applied the proposed approach in a flood case in the metropolis of São Paulo. The proposed approach is efficient in uncovering the dynamics in human movements and the underlying spatial structure. It adds to our understanding of the resilience process in urban disasters.
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Yan Wang, Hong Huang, Lida Huang, Minyan Han, Yiwu Qian, & Boni Su. (2017). An Agile Framework for Detecting and Quantifying Hazardous Gas Releases. 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. 42–49). Albi, France: Iscram.
Abstract: In response to the threat of hazardous gas releases to public safety and health, we propose an agile framework for detecting and quantifying gas emission sources. Emerging techniques like high-precision gas sensors, source term estimation algorithms and Unmanned Aerial Vehicles are incorporated. The framework takes advantage of both stationary sensor network method and mobile sensing approach for the detection and quantification of hazardous gases from fugitive, accidental or deliberate releases. Preliminary results on street-level detection of urban natural gas leakage is presented. Source term estimation is demonstrated through a synthetic test case, and is verified using Cramér-Rao bound analysis.
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Xiujuan Zhao, Jianguo Chen, Peng Du, Wei Xu, Ran Liu, & Hongyong Yuan. (2019). Location-allocation model for earthquake shelter solved using MPSO algorithm. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Constructing shelters in suitable quantities, with adequate capacities and at the right locations is essential for evacuees under earthquake disasters. As one of the disaster management methods, constructing shelters can help to significantly reduce disruption and devastation to affected population. Mathematical models have been used to solve this problem allied with a heuristic optimization algorithm. The optimization of evacuation efficiency, as one of the most important objectives, has many expressive forms, such as minimizing evacuation distance and evacuation time. This paper proposes a new model that aims to minimize evacuation time with a new calculation method and to maximize total evacuees? comfort level. The modified particle swarm optimization (MPSO) algorithm is employed to solve the model and the result is compared with a model that calculated evacuation time differently and a model without distance constraint, respectively.
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Xiujuan Zhao, Graham Coates, & Wei Xu. (2017). Solving the earthquake disaster shelter location-allocation problem using optimization heuristics. 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. 50–62). Albi, France: Iscram.
Abstract: Earthquakes can cause significant disruption and devastation to populations of communities. Thus, in the event of an earthquake, it is necessary to have the right number of disaster shelters, with the appropriate capacity, in the right location in order to accommodate local communities. Mathematical models, allied with suitable optimization algorithms, have been used to determine the locations at which to construct disaster shelters and allocate the population to them. This paper compares the use of two optimization algorithms, namely a genetic algorithm and a modified particle swarm optimization, both of which have advantages and disadvantages when solving the disaster shelter location-allocation problem.
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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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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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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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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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Xiaofeng Hu, Shifei Shen, & Jiansong Wu. (2012). Modeling of attacking and defending strategies in situations with intentional threats. 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: Intentional threats including terrorism have become a worldwide catastrophe risk since recent years. To protect the cities from being attacked, the macro-level study of decision analysis should be given more considerations. In this paper, we proposed a model for describing the strategic game between attackers and defenders based on the methodology of matrix game. This model can be employed to determine which target will be selected by attackers and which attacking strategy and defending strategy will be chosen by attackers and defenders respectively. Furthermore, the defenders of the city can use this model to set priorities among their defending strategies. The importance of this work is to establish a reasonable framework for modeling the attacking and defending strategies rather than assessing the real risk of urban targets, so the model is illustrated by using fictitious numbers. The model proposed in this paper can provide scientific basis for macroscopic decision making in responding to intentional threats. © 2012 ISCRAM.
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Victor A. Bañuls, Cristina López-Vargas, Fernando Tejedor, Murray Turoff, & Miguel Ramirez de la Huerga. (2016). Validating Cross-Impact Analysis in Project Risk Management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Companies work increasingly more on projects as a means of executing organizational decisions. However, too many enterprise projects result in failure. Hence, firms should follow a risk management method that drives their projects toward success. Nevertheless, project managers often deal with risks intuitively. This is partly because they lack the proper means to correctly manage the underlying risks which affect the entire cycle of their projects. Therefore, one purpose is to identify the critical events that managers may encounter before the beginning of the project and during its development. In addition, we propose CIA-ISM to represent existing relationships between the unforeseen events in the project?s lifetime and their key performance indicators. This also predicts the influence of risks on project performance over time by means of scenarios. The tool proposed would thus help practitioners to manage enterprise projects risks in a more effective and proactive way. We have validated the predictive capability of the CIA-ISM model with 22 real projects. The results show a high level of predictive capability in terms of risk analysis and key performance indicators.
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Victor A. Bañuls, Andrzej M. Skulimowski, & José Antonio Román Begines. (2021). Disaster Resilience Modeling of Municipal Water Supply Infrastructures in the Context of Atmospheric Threats. 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. 198–207). Blacksburg, VA (USA): Virginia Tech.
Abstract: The resilience of water supply infrastructure (WSI) is of utmost importance as threats to predominantly, although not exclusively, urban WSI may accompany virtually all kinds of natural disasters. In this paper, we present some of the challenges posed by climate change in modeling emergencies in WSIs. Climate change is a global phenomenon that significantly impacts global lifestyle. It is expected that increase in global temperatures causes sea levels to rise, increases the number of extreme weather events such as floods, droughts, and storms while highly impacting WSI. In this respect, the challenge is to be prepared for the unexpended by modeling various complex scenarios. Only with a multidisciplinary approach at the global, regional, national, and local levels, can success be achieved. We discuss some of the specific challenges posed by climate change in modeling emergencies in WSIs with a case study modeled using EMERTIC. EMERTIC is a software based on AI and scenarios, that is aimed at supporting decision making at different stages of the Emergency Management cycle.
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Usman Anjum, Vladimir Zadorozhny, & Prashant Krishnamurthy. (2021). TBAM: Towards An Agent-Based Model to Enrich Twitter Data. 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. 146–158). Blacksburg, VA (USA): Virginia Tech.
Abstract: Twitter is widely being used by researchers to understand human behavior, e.g. how people behave when an event occurs and how it changes their microblogging pattern. The changing microblogging behavior can have an important application in the form of detecting events. However, the Twitter data that is available has limitations in it has incomplete and noisy information and has irregular samples. In this paper we create a model, calledTwitter Behavior Agent-Based Model (TBAM)to simulate Twitter pattern and behavior using Agent-Based Modeling(ABM). The generated data can be used in place or to complement the real-world data and improve the accuracy of event detection. We confirm the validity of our model by comparing it with real data collected from Twitter
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Toshihiro Osaragi, & Noriaki Hirokawa. (2019). Simulation Analysis of Fire Hydrant Usability Levels after Large Earthquake. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Since large earthquakes can disrupt water supply networks, it is essential to gain an understanding of the expected
usability of fire hydrants in post-quake firefighting activities. In this study, data about water supply networks was
collected and a water outage simulation model was constructed in order to predict the likelihood that individual
fire hydrants would become unusable in the wake of a large earthquake. The water outage simulation model was
integrated with a previously developed urban zone damage simulation and a fire department activity simulation
in order to carry out a simulation-based analysis of the 23 wards of Tokyo, after which a quantitative analysis of
the relation-ship between use of fire hydrants and the number of buildings lost to fire was performed. This analysis
revealed the benefits of hardening water lines against earthquakes, fire hydrant usage variations depending on
locality, and the benefits of using water pressure sensors to identify usable fire hydrants.
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Toshihiro Osaragi, Koji Ogino, Noriaki Hirokawa, & Takuya Oki. (2022). Severity of Crowding at Evacuation Shelters after a Major Earthquake. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 22–43). Tarbes, France.
Abstract: A number of residents are presumed to evacuate to shelters after a large earthquake. However, the congestion of evacuation shelters has not been enough discussed. In this paper, we propose an evacuation behavior model, which includes sub-models on building damage, water-supply failure, power failure, fire damage, and elevator stall. Using the model estimated using the survey data of the past earthquakes, we discuss the congestion of evacuation shelters under the assumption of Tokyo Bay northern earthquake. Finally, we discuss improvement of water pipes for earthquake resistance to reduce the congestion degree of evacuation shelters, which varies according to regional vulnerability.
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Toshihiro Osaragi. (2018). Crowding of Various Facilities Relevant to Supporting People Who Have Difficulty Returning Home after a Large Earthquake. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 45–59). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: When a large earthquake occurs, many people are presumed to have difficulty in returning home. However, no research has been achieved yet to discuss the congestion of supporting facilities for stranded people in terms of site, the number and spatial distribution. In this study, we construct a simulation model, which describes people's behavior such as returning home or going to other facilities after an earthquake occurs. Using the model, we estimate the congestion of facilities which varies according to day of the week or the time when the event occurs, and demonstrate the effective methods for reducing the congestion, which include offering information for people and cooperation of private institutions.
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Toshihiro Osaragi. (2020). Accessibility Evaluation of Specific Emergency Transportation Roads and Benefits of Seismic Retrofits on Buildings Adjoining Roads. 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. 143–156). Blacksburg, VA (USA): Virginia Tech.
Abstract: Securing the accessibility of emergency vehicles using specific emergency transportation road (SETR) is crucial for the rapid activities of emergency vehicles after a large earthquake. In this paper, we construct a simulation model that describes collapse of roadside buildings and following street blockages, and evaluate the accessibility of emergency vehicles. Performing the simulations, we demonstrate the effects of quake-resistant-conversion of roadside buildings as follows: (1) the accessibility of emergency vehicles using SETR is not good enough under the current situation, but (2) can be significantly improved by performing seismic retrofit of buildings according to seismic index of building structure.
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Tongshen Zheng, Shunjiang Ni, Shifei Shen, Yan Wang, & Yang Tai. (2016). Numerical Study of Radioactive Pollutants Dispersion in Radioactive ?Dirty Bomb? Events. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The simulation of radioactive pollutants dispersion is critical for emergency response of the nuclear terrorism. The radioactive ?dirty bomb?, also called radiological dispersion device (RDD), produced and used by the terrorist to make fearful and radioactive pollution in general, has a great risk on humans. Numerical investigation of the impact of different configurations on radioactive pollution release and dispersion in urban buildings is made in this paper. The numerical simulations used the OpenFOAM, a free and open source software for computational fluid dynamics (CFD), and the simulations can be implanted to the information system of the nuclear terrorism emergency decision support system(EDSS) as the consequence assessment subsystem conveniently. The study showed that the configurations of building canyon and the position relationship of the source item and the buildings both affect the concentration distributions around the buildings.
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Tobias Meuser, Lars Baumgärtner, & Patrick Lieser. (2021). Pandemic Skylines: Digital Twins for More Realism in Epidemic Simulations. 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. 133–145). Blacksburg, VA (USA): Virginia Tech.
Abstract: In the recent months, many measures have been taken by governments to fight the COVID-19 pandemic. Due to the unknown properties of the disease and a lack of experience with handling pandemics, the effectiveness of measures taken was often hard to evaluate the effectiveness of measures, leading to inefficient measures and late execution of efficient measures. Many models have been proposed to evaluate the performance of these measures on the spreading of a pandemic, but these models are commonly vastly simplified and, thus, limited in expressiveness. To extend the expressiveness of the models, we developed a epidemic simulation inside of a flexible and scalable city simulation game to analyse the counter measures to a pandemic in this city and spot common places of infection on a microscopic level. The configurability of our developed epidemic simulation will also be useful for potential future pandemics.
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Till Sahlmüller, & Bernd Hellingrath. (2022). Measuring the Resilience of Supply Chain Networks. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 55–67). Tarbes, France.
Abstract: With increasing supply chain complexity, it gets more likely that disruptions ripple through the supply chain network, affecting supply chain performance. As the severity of disruptions depends on the supply chain network structure, it is important to assess the network structure in terms of its resilience. This article presents the results of a literature review (LR) to provide a comprehensive overview of measures used for evaluating the resilience of supply chain networks. The results indicate a wide range of measures applied in literature, focusing on either nodes, paths, or subgraphs of the network. The identified measures are compared regarding the structural characteristics they study and the aspects of supply chain performance they investigate.
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Takuya Oki, & Toshihiro Osaragi. (2016). Wide-area Evacuation Difficulty in Densely-built Wooden Residential Areas. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: In aiming to decrease the number of casualties and people with difficulty in wide-area evacuations due to a large earthquake, it is highly important to visualize and quantify the potential danger in residential areas. In this paper, we construct a multi-agent simulation model, which describes property damage (such as building-collapse, the spread of fire and blocking of streets) and people?s evacuation behavior after an earthquake occurring. Using this simulation model, we quantify the wide-area evacuation difficulty in densely-built wooden residential areas, and evaluate the past project to improve buildings and streets based on this indicator. Furthermore, we demonstrate the effects of adding new evacuation routes between two intersections of streets with narrow width and long distance. Through these case studies, the effectiveness of our simulation model on urban disaster mitigation planning is shown.
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Takuya Oki, & Toshihiro Osaragi. (2017). Evaluation of Conversion to Quake-Resistant Buildings in Terms of Wide-Area Evacuation and Fire-Brigade Accessibility. 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. 25–41). Albi, France: Iscram.
Abstract: It is important to evaluate the effects of improving the disaster vulnerability of towns by using various indices related to human damage. In this paper, we focus on conversion of low quake-resistant old buildings. Firstly, we construct a simulation model, which describes property damage (such as building-collapse and street-blockage), wide-area evacuation behavior, and fire-brigade's activities immediately after a large earthquake occurs. Next, using the simulation model, we estimate the travel time required for evacuation, the number of evacuees trapped on streets (or in blocks), and the access time of fire-brigades to fires in case that the ratio of quake-resistant buildings in the area increases to a certain value. Based on the results, we discuss the effects by converting old buildings into quake-resistant ones on reducing the difficulty in wide-area evacuation and improving the accessibility of fire-brigades in multiple study areas with different characteristics.
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Simon French, Nikos Argyris, Jim Q. Smith, Stephanie Haywood, & Matthew C. Hort. (2017). Uncertainty Handling during Nuclear Accidents. 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. 15–24). Albi, France: Iscram.
Abstract: In the years following Chernobyl, many reports and projects reflected on how to improve emergency management processes in dealing with an accidental offsite release of radiation at a nuclear facility. A common observation was the need to address the inevitable uncertainties. Various suggestions were made and some of these were researched in some depth. The Fukushima Daiichi Disaster has led to further reflections. However, many of the uncertainties inherent in responding to a threatened or actual release remain unaddressed in the analyses and model runs that are conducted to support the emergency managers in their decision making. They are often left to factor in allowances for the uncertainty through informal discussion and unsupported judgement, and the full range of sources of uncertainty may not be addressed. In this paper, we summarise the issues and report on a project which has investigated the handling of uncertainty in the UK's national crisis cell. We suggest the R&D programmes needed to provide emergency managers with better guidance on uncertainty and how it may affect the consequences of taking different countermeasures.
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Robert Zinke, Laura Künzer, Benjamin Schröder, & Christina Schäfer. (2017). Integrating Human Factors into Evacuation Simulations – Application of the Persona Method for Generating Populations. 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. 127–138). Albi, France: Iscram.
Abstract: For assessing evacuation dynamics in disaster situations, current approaches of pedestrian simulations increasingly include additional human characteristics. One aim is to assess realistic effects of structural changes of an infrastructure on evacuation behavior displayed by users. Creating agents with supplementary physical and psychological human characteristics and assembling the agents in accordance to the user's population may be beneficial not only to support decision making. The analysis of simulated effects of, e.g., informational strategies will foster crisis and disaster management. This paper combines knowledge about users in subway systems and highlights benefits of using the Persona method to improve objectivity in the specification of different user types. Persona method is adapted to pedestrian simulation. Using data from the authors´ field studies, personas are developed and implemented for an evacuation simulation. First findings suggest that including personas into pedestrian simulation influences the results with respect to the required safe evacuation time (RSET).
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