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A flood evacuation represents a complex geographic phenomenon that includes comprehensive interactions among humans, the flood and urban environments; thus, the simulation of flood evacuations requires crowd simulation models to be coupled with flood models. This paper studies the human-environment relationship during flooding and promotes a simula...
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... case study area, namely, Niaodao Island, is located on the Hunhe River within the city of Shenyang, Liaoning Province, China. Niaodao Island is a tourist destination, which covers an area of 49.26 hectares (shown in Figure 1). According to the statistical data for 25 April 2017, Niaodao Island can accommodate more than 6,000 visitors daily in the peak tourist season. ...
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Recently many runoff models based on cellular automaton (CA) have been developed to simulate floods; however, the existing models cannot be readily applied to complex urban environments. This study proposes a novel rainfall-runoff model based on CA (RRCA) to simulate inundation. Its main contributions include a fine runoff generation process that c...
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... In Li et al. [43], the authors explore the simulation of flood evacuation, a complex geographic process involving the dynamic attributes of floods, field patches, and their interactions with crowd behaviors. They introduce a Cellular Automata and Multi-Agent System (CA-MAS) model to integrate water evolution, land cover, objective domain, crowd, and individual movement data. ...
The topic of flood phenomena has always been of considerable importance due to the high risks it entails, both in terms of potential economic and social damage and the jeopardizing of human lives themselves. The spread of climate change is making this topic even more relevant. This work aims to contribute to evaluating the role that human factors can play in responding to critical hydrogeological phenomena. In particular, we introduce an agent-based platform for analyzing social behaviors in these critical situations. In our experiments, we simulate a population that is faced with the risk of a potentially catastrophic event. In this scenario, citizens (modeled through cognitive agents) must assess the risk they face by relying on their sources of information and mutual trust, enabling them to respond effectively. Specifically, our contributions include (1) an analysis of some behavioral profiles of citizens and authorities; (2) the identification of the "dissonance between evaluation and action" effect, wherein an individual may behave differently from what their information sources suggest, despite having full trust in them in situations of particular risk; (3) the possibility of using the social structure as a "social risk absorber", enabling support for a higher level of risk. While the results obtained at this level of abstraction are not exhaustive, they identify phenomena that can occur in real-world scenarios and can be useful in defining general guidelines.
... The ability of CAs to simulate complex systems or processes makes them widely applicable to several phenomena from the physics, chemistry, and geography fields. For example, CAs with different numbers of possible states, connected neighbors, and rules for computing new states are used to simulate flood risks, vegetation changes, land use changes, forest fires, or other hazards (Piegari and Di Maio 2014, Iudin et al. 2015, Li et al. 2019, Lupiano et al. 2020, Zhai et al. 2020, Torres et al. 2022). A landslide system is a complex system characterized by nonlinearity, randomness, anisotropy, and self-similarity (Ma et al. 2013). ...
Predicting landslide hazards benefits geological disaster prevention and control. A novel cellular automaton (CA) integrating spatial case-based reasoning (SCBR), namely SCBR-CA, is proposed in this paper to predict landslide hazards at a local scale. The proposed model not only extracts spatial scene features for computations but also achieves dynamic prediction, which means that only one input is needed to obtain continuous predictions. Experiments were performed in Lushan, Sichuan, China. After using a convolutional neural network (CNN) to obtain the initial static landslide hazard zoning results, the landslide hazard zoning results for 2016–2025 were predicted with the SCBR-CA model. For comparison, a CA combined with a CNN (CNN-CA), was introduced. The area under the curve (AUC) of the receiver operating characteristic curve and Moran’s I index were used to assess the performance of the model. The experimental results showed that SCBR-CA yields slightly better AUC and Moran’s I index values than CNN-CA, and the dynamically predicted landslide hazard zoning results are equivalent or superior to those of static zoning, which indicates that the SCBR-CA model effectively predict local landslide hazards.
... Different protocols of involvement of participants are used in literature [46,48,53]. Usually, a number higher than 30 participants is recommended for this kind of experiment. ...
Various methodologies and technologies have been developed and tested to train communities for natural hazards and investigate human behaviour. The combination of Virtual Reality (VR) and Serious Games (SG) represents a promising solution to expose communities to different hazardous scenarios in a totally safe way and without exposing the testers to any real risks. Previous studies tested VR SG for several different natural hazards and safety training scenarios, but only a few applications have been proposed within the context of flood safety training. Furthermore, comprehensive prototyping works aimed at evaluating VR SG applications in terms of knowledge acquisition, self-efficacy and user experience, are still needed. This work proposes a novel non-immersive VR SG in the context of users' safety in the event of flooding in the urban built environment, pursuing the users' safety training. The proposed application is based on several modules, which can be combined to form different storylines and training objectives. The VR SG capabilities are demonstrated here by firstly considering one significant storyline. Results show a significant increase in self-efficacy and safety knowledge after the VR experience, thus suggesting the possibility to exploit it for increasing users' awareness and preparedness. Furthermore, results also demonstrate the existence of similarities between real-world behaviours and VR choices by the tested individuals, thus suggesting how an application of this kind could also be used to support the development and validation of flood evacuation simulators.
... Stochastic programming methods allow minimizing the risk and time spent on the road to develop evacuation recommendations [54]. (C) Uncertainty in the behavior of self-evacuating people when choosing evacuation routes (ER) and EP is studied on the basis of game-theoretic and agent-based modeling [47,50,53,[55][56][57]. Simulating individual behavior over large areas using complex behavior models is computationally intensive. ...
... An important direction is to identify the negative impact of floods on the health of the evacuated population [67,68]. It should be emphasized that such studies are carried out for specific areas, since each real water body has characteristic features [26,31,[41][42][43]48,50,53,[55][56][57][58]65]. ...
Extreme flooding of the floodplains of large lowland rivers poses a danger to the population due to the vastness of the flooded areas. This requires the organization of safe evacuation in conditions of a shortage of temporary and transport resources due to significant differences in the moments of flooding of different spatial parts. We consider the case of a shortage of evacuation vehicles, in which the safe evacuation of the entire population to permanent evacuation points is impossible. Therefore, the evacuation is divided into two stages with the organization of temporary evacuation points on evacuation routes. Our goal is to develop a method for analyzing the minimum resource requirement for the safe evacuation of the population of floodplain territories based on a mathematical model of flood dynamics and minimizing the number of vehicles on a set of safe evacuation schedules. The core of the approach is a numerical hydrodynamic model in shallow water approximation. Modeling the hydrological regime of a real water body requires a multi-layer geoinformation model of the territory with layers of relief, channel structure, and social infrastructure. High-performance computing is performed on GPUs using CUDA. The optimization problem is a variant of the resource investment problem of scheduling theory with deadlines for completing work and is solved on the basis of a heuristic algorithm. We use the results of numerical simulation of floods for the Northern part of the Volga-Akhtuba floodplain to plot the dependence of the minimum number of vehicles that ensure the safe evacuation of the population. The minimum transport resources depend on the water discharge in the Volga river, the start of the evacuation, and the localization of temporary evacuation points. The developed algorithm constructs a set of safe evacuation schedules for the minimum allowable number of vehicles in various flood scenarios. The population evacuation schedules constructed for the Volga-Akhtuba floodplain can be used in practice for various vast river valleys.
... Many evacuation modeling techniques have been applied to tsunami (or flood) evacuation simulation, such as geographic information system (GIS)-based model (CRATER 2005;Dewi 2012; Wood et al. 2016;Benchekroun and El Mouraouah 2018), distinct element method (DEM)-based model (Gotoh et al. 2004(Gotoh et al. , 2009Rahman et al. 2014;Abustan 2013), cellular automata (CA) model (Li et al. 2019b), and agent-based model (Usuzawa et al. 1997;Fujioka et al. 2002;Lämmel 2011;Wijerathne et al. 2013). In addition, the system dynamics (SD) model (Ahmad and Simonovic 2000a;Simonovic and Ahmad 2005;Berariu et al. 2016) that has been used for flood management might also be applied to tsunami evacuation simulation. ...
... Although a lot of CA models exist for the building evacuation simulation, few CA models have been developed to simulate flood evacuation or tsunami evacuation. A model was proposed to simulate crowd evacuations in flood disasters by combining CA and a multi-agent system (Li et al. 2019b). When an earthquake occurs, many people have to leave the coast as soon as possible for avoiding the tsunami. ...
Earthquake-induced tsunami can be very destructive involving significant loss of life. Evacuation to safety zones is regarded as one of the most effective ways to save lives from the tsunami strike due to the limited effectiveness of structural countermeasures. However, it is extremely challenging to successfully evacuate many people under the multi-hazard environment within a condensed time frame, especially under the near-field tsunami. Proper evacuation planning is crucial to support effective evacuation and reduce casualty. For effective evacuation planning, it is important to better understand the complex evacuation behavior for recommending proper response and behavior in an emergency. Also, it is important to have a clear picture of evacuation risk (e.g., measured in terms of expected casualty rate within a certain time frame) for informing policy and decision-making. Furthermore, it is important to identify effective pre-event mitigation strategies for effective risk reduction.
Important limitations exist in current research on the above aspects. Tsunami evacuation simulation using the agent-based model has been used to investigate the complex evacuation behavior; however, existing agent-based evacuation models usually neglect or simplify many important factors and/or mechanisms associated with the evacuation. The neglect or simplification would make the evacuation simulation less realistic and hence a good understanding of evacuation behavior challenging. For the quantification of tsunami evacuation risk, a systematic framework that can address complex evacuation models and uncertainty (including aleatory and epistemic uncertainties) models is needed; however, no such framework has been developed for the quantification of tsunami evacuation risk. Also, some important uncertainties such as that in the seismic damage to the bridge are usually neglected or the uncertainty quantification is simplified. In this case, it would be difficult to assess the evacuation risk accurately and provide a clear picture of the evacuation risk. For effective pre-event evacuation risk mitigation, the effectiveness of different mitigation strategies needs to be quantitatively evaluated to identify more effective strategies. However, the effectiveness of the mitigation strategy is usually evaluated more qualitatively than quantitatively. Furthermore, the evaluation is typically conducted without systematically considering various uncertainties, which makes the identified strategies not robust to uncertainties. In tsunami evacuation risk assessment and mitigation, risk evaluation using general stochastic simulation techniques (e.g., Monte Carlo simulation) typically entails significant computational challenges. Efficient algorithms are needed to alleviate such computational challenges and facilitate such tasks.
To bridge the above knowledge gaps, this research proposes a generalized framework for simulation-based tsunami evacuation risk assessment and risk-informed mitigation. The framework is built layer by layer through integrating tsunami evacuation simulation using agent-based modeling (ABM) technique, simulation-based evacuation risk assessment, sensitivity analysis of evacuation risk, and risk-informed evaluation of mitigation strategies. An improved agent-based tsunami evacuation model is developed for more realistic tsunami evacuation simulation by incorporating many of the typically neglected or simplified but important factors and/or mechanisms in the evacuation. Using the proposed agent-based evacuation model, a simulation-based framework is proposed to quantify the evacuation risk, in which various uncertainties (including aleatory and epistemic uncertainties) associated with the evacuation are explicitly considered and modeled by proper selection of probability distribution models. Sensitivity analysis of evacuation risk with respect to the epistemic uncertainty is performed, and the sensitivity information can be used to guide effective epistemic uncertainty reduction and hence for more accurate risk assessment. Also, sensitivity analysis is performed to identify critical risk factors, and the sensitivity information can be used to guide effective evacuation modeling and selection of candidate risk mitigation strategies. Risk-informed evaluation of different types of candidate mitigation strategies (including infrastructural and non-infrastructural strategies) is conducted to identify more effective strategies that are robust to uncertainties. Efficient sample-based approaches are developed to alleviate the computational challenges in evacuation risk assessment, sensitivity analysis, and risk-informed evaluation of mitigation strategies. As an illustrative example, the proposed framework is applied to tsunami evacuation risk assessment and risk-informed mitigation for the coastal community of Seaside, Oregon.
... Concerning the type of scenarios and strategies tested with the model, they can be of different types: hazard scenarios (Battegazzorre et al. 2021, Veeraswamy et al. 2018, different parameters for the population -e.g. density/number (Li et al. 2019, Wang et al. 2020, Nakasaka et al. 2020, psychological/physical characteristics (Yamazaki et al. 2017, Wang et al. 2020, West and Sherry 2020, knowledge of the shelters (Sun et al. 2021), information/communication (Parikh et al. 2017), car use (Aguilar et al. 2019, Kim andCho 2020), group composition (Pan et al. 2021) or evaluation of different policies (Kim et al. 2017, Yin et al. 2020, Bianchin and Pasqualetti 2020, Oh et al. 2021, Al-Zinati and Zalila-Wenkstern 2018. Regarding the latter type, Bianchin and Pasqualetti (2020) proposes to optimize the duration of traffic lights to minimize congestion. ...
At a time when the impacts of climate change and increasing urbanization are making risk management more complex, there is an urgent need for tools to better support risk managers. One approach increasingly used in crisis management is preventive mass evacuation. However, to implement and evaluate the effectiveness of such strategy can be complex, especially in large urban areas. Modeling approaches, and in particular agent-based models, are used to support implementation and to explore a large range of evacuation strategies, which is impossible through drills. One major limitation with simulation of traffic based on individual mobility models is their capacity to reproduce a context of mixed traffic. In this paper, we propose an agent-based model with the capacity to overcome this limitation. We simulated and compared different spatio-temporal evacuation strategies in the flood-prone landlocked area of the Phúc Xá district in Hanoi. We demonstrate that the interaction between distribution of transport modalities and evacuation strategies greatly impact evacuation outcomes. More precisely, we identified staged strategies based on the proximity to exit points that make it possible to reduce time spent on road and overall evacuation time. In addition, we simulated improved evacuation outcomes through selected modification of the road network.
... Different protocols of involvement of participants are used in literature [46,48,53]. Usually, a number higher than 30 participants is recommended for this kind of experiment. ...
... developed an ABM to simulate city-scale evacuation during a flood event. The evacuation simulation was coupled with a hydrodynamic model and the authors experimented different escaping scenarios based on the 2011 Brisbane flood [27]. present a model combining cellular automata and ABM to simulate crowd evacuations in flood disasters. ...
Flood management is particularly important for many urban territories. In order to assess the interest of different risk mitigation strategies, it is necessary to consider the human behavior. Different models and approaches are available to model and simulate people behaviors during a flood event. Despite the considerable recent progress of these models, none of them succeeds in answering all the required challenges: (1) simulate the flood event, (2) integrate geographical information, (3) take into account complex behaviors for inhabitants considering emotion and partial knowledge, (4) enable different strategies for inhabitants, (5) take into account the degradation of infrastructures and its impact on their functioning, and (6) ensure the genericity and flexibility of the model in order to be able to apply it to any territory. In order to meet these challenges, we provide a new Agent based Model, called SiFlo. In this paper, we present this model and an application to La Ciotat (France).
... Within this line, the field of crowd simulation has also gained strength, and we also find some studies on it using VR and MAS [57][58][59][60][61][62][63][64][65][66][67][68]. This type of simulation has multiple purposes: planning emergency plans [69][70][71][72], improvement of the work environment [73][74][75][76][77][78], improvement of the educational environment [79][80][81][82][83][84][85][86], people training [87][88][89][90][91][92][93][94][95], interactions between humans and avatars [96,97], smart buildings and commerce simulation [98,99], etc. ...
... In the case of emergency plans, Yi Li et al. [69] studied the human environment during flooding and promoted a simulation model that combines cellular automata and a MAS to simulate crowd evacuations in flood disasters. The model proposed to integrate the evolution of water, land cover, objective domain, crowd, and individual movements data. ...
... These applications are related to different purposes that are described and in which that section has been divided: videogames development [30][31][32][33][34][35][36][37][38][39], robot simulation [40,41], interactive virtual environments development [42][43][44][45], human behavior simulation , dissemination of cultural heritage [100,101], urban m development of autonomous vehicles [107,108], and machinery simulation [109][110][111] (Figure 5). Also, simulation of human behavior can be divided into subcategories: crowds simulation [57][58][59][60][61][62][63][64][65][66][67][68], emergency plans [69][70][71][72], work environment [73][74][75][76][77][78], educational environment [79][80][81][82][83][84][85][86], staff training [87][88][89][90][91][92][93][94][95], interactions between humans and avatars [96,97], and smart buildings and commerce [98,99]. ...
Multi-agent systems integrate a great variety of artificial intelligence techniques from different fields, these systems have made it possible to create intelligent systems more efficiently. On the other hand, virtual reality applications are accepted as viable techniques in different areas such as visualization, simulation, design, and research. The combined use of these two technologies has led to the development of realistic and interactive applications. This work aims to do a Systematic Mapping Study (SMS) relying on the guidelines of Kitchenham and Petersen to analyze the state of the art of VR applications using multi-agent systems. Inclusion and exclusion criteria have been applied to identify relevant papers, 82 articles were selected and categorized according to the publication type, the research type, the asset type, and the purpose of the work. A complete review of the 82 selected articles was performed, based on the research questions that were established. This review made it possible to clarify the open lines of research that exist and to know where research in this field can be directed.
... This tool is commonly used in ecology, environmental, natural disasters, risk predictions, etc. As a powerful tool for highly complex geographical phenomena, many have continued to expand the standard CA model by combining it with fractal theory, the multi-factor evaluation model, artificial neural networks, Markov chain, and multi-agent, etc. [18][19][20]. ...
Under the background of the ecological civilization era, rapidly obtaining coal mining information, timely assessing the ecological environmental impacts, and drafting different management and protection measures in advance to enhance the capacity of green mine construction have become the urgent technical problems to be solved at present. Simulating and analyzing mining subsidence is the foundation for a land reclamation plan. The Cellular Automata (CA) model provides a new tool for simulating the evolution of mining subsidence. This paper takes a mine in East China as a research area, analyses the methods and measures for developing a model of mining subsidence based on the theories of CA and mining technology, then discusses the results of simulation from different aspects. Through comparative analysis, it can be found that the predicted result is well consonant with the observation data. The CA model can simulate complex systems. The system of mining subsidence evolution CA is developed with the support of ArcGIS and Python, which can help to realize data management, visualization, and spatial analysis. The dynamic evolution of subsidence provides a basis for constructing a reclamation program. The research results show that the research methods and techniques adopted in this paper are feasible for the dynamic mining subsidence, and the work will continue to do in the future to help the construction of ecological civilization in mining areas.
