Journal articles on the topic 'Pedestrian dynamics, crowd, agent-based approach, simulation'
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1
Li, Liang, Hong Liu, and Yanbin Han. "An approach to congestion analysis in crowd dynamics models." Mathematical Models and Methods in Applied Sciences 30, no. 05 (April 16, 2020): 867–90. http://dx.doi.org/10.1142/s0218202520500177.
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This paper presents a novel approach to quantitatively analyzing pedestrian congestion in evacuation management based on the Hughes and social force models. An accurate analysis of crowds plays an important role in illustrating their dynamics. However, the majority of the existing approaches to analyzing pedestrian congestion are qualitative. Few methods focus on the quantification of the interactions between crowds and individual pedestrians. According to the proposed approach, analytic tools derived from theoretical mechanics are applied to provide a multiscale representation of such interactions. In particular, we introduce movement constraints that illustrate the macroscopic and microscopic states of crowds. Furthermore, we consider pressure propagation and changes in the position of pedestrians during the evacuation process to improve the accuracy of the analysis. The generalized force caused by the varied density of pedestrians is applied to calculate the final congestion. Numerical simulations demonstrate the validity of the proposed approach.
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Abdelghany, Ahmed, Hani Mahmassani, Khaled Abdelghany, Hasan Al-Ahmadi, and Wael Alhalabi. "Incidents in high-volume elongated crowd facilities: A simulation-based study." SIMULATION 95, no. 9 (September 11, 2018): 823–43. http://dx.doi.org/10.1177/0037549718794882.
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This paper presents the main findings of a simulation-based study to evaluate incidents in pedestrian/crowd tunnels and similar elongated confined facilities, with high-volume heterogeneous traffic. These incidents, when occur, imposes hazardous conditions that always result in significant number of fatalities. The aim of this study is to understand how these facilities perform under different irregular scenarios and possibly identify potential causes of accidents. The problem of studying incidents in large-scale high-volume pedestrian facilities is that these incidents are difficult to expect or replicate. Thus, studying these facilities through real-life scenarios is almost impossible. Accordingly, a micro-simulation assignment model for multidirectional pedestrian movement is used for this purpose. The model adopts a Cellular Automata (CA) discrete system, which allows detailed representation of the pedestrians’ walkways in the tunnel. The modeling approach captures crowd dynamics through representation of behavioral decisions of heterogeneous pedestrians at the individual level. Several experiments are conducted to study the pedestrian flow in the proposed tunnel considering different operational scenarios including demand levels, heterogeneous traffic, evacuation scenario, and tunnel blockage. Results show that flow of large pedestrian volumes through a long confined linear structure, such as a tunnel, are subject to the same flow dynamics as we observe with vehicular traffic. In particular, they are subject to the formation of “clumps” and shock waves that can rapidly propagate and lead to inefficient operation, including flow breakdown with stop-and-go waves.
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Kim, Daewa, Kaylie O’Connell, William Ott, and Annalisa Quaini. "A kinetic theory approach for 2D crowd dynamics with emotional contagion." Mathematical Models and Methods in Applied Sciences 31, no. 06 (April 17, 2021): 1137–62. http://dx.doi.org/10.1142/s0218202521400030.
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In this paper, we present a computational modeling approach for the dynamics of human crowds, where the spreading of an emotion (specifically fear) has an influence on the pedestrians’ behavior. Our approach is based on the methods of the kinetic theory of active particles. The model allows us to weight between two competing behaviors depending on fear level: the search for less congested areas and the tendency to follow the stream unconsciously (herding). The fear level of each pedestrian influences their walking speed and is influenced by the fear levels of their neighbors. Numerically, we solve our pedestrian model with emotional contagion using an operator splitting scheme. We simulate evacuation scenarios involving two groups of interacting pedestrians to assess how domain geometry and the details of fear propagation impact evacuation dynamics. Further, we reproduce the evacuation dynamics of an experimental study involving distressed ants.
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Wirth, Ervin, and György Szabó. "Overlap-avoiding Tickmodel: an Agent- and GIS-Based Method for Evacuation Simulations." Periodica Polytechnica Civil Engineering 62, no. 1 (June 14, 2017): 72. http://dx.doi.org/10.3311/ppci.10823.
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Evacuation simulation is a method to determine evacuation times for areas, buildings, or vessels. It is based on the simulation of crowd dynamics and pedestrian motion; in this paper, we investigated the evacuation characteristics with a new motion model. The motion model and modeling space were implemented in an agent-based environment. The model is simple and generally applicable, it navigates the agent towards the destinations (safe zones) in a mixed macro-micro approach. The simulations were tested in a geospatially modeled lecture hall of the Budapest University of Technology and Economics (BME). The evacuation times and the panic rate were both estimated; a new way of measurement was applied for panic. Finally, conclusions were made on the person count ~ evacuation time and person count ~ panic rate relations. The paper introduces the key factors of this complex modeling phenomenon and demonstrates how to set up an agent-based evacuation model. The results can simulate the real phenomenon and constitute valuable assets for decision-making in public safety issues (architectural design, evacuation protocol, regulations of space).
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Mitrovic, Tanja, Vesna Stojakovic, and Milica Vracaric. "Simulation of pedestrian accessibility to assess the spatial distribution of urban amenities." Spatium, no. 00 (2022): 2. http://dx.doi.org/10.2298/spat210429002m.
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A city can be perceived as a framework for the everyday activities of its residents, whose movements create complex network patterns as consequences of their individual decisions. Given that there are apparent differences in the use of urban amenities among residents of different ages, we examined the spatial distribution of urban amenities with regard to the preferences of various age groups and the pedestrian accessibility of amenities. In this paper, we propose an algorithm for detecting the most favorable combinations for the spatial distribution of urban amenities, in order to minimize the total walking distances and maximum frequencies of pedestrians of different age groups. The proposed method focuses on the parametric interpretation of various age groups, their preferences for urban amenities, the mutual proximity between residential and non-residential areas, and crowd intensity. Since residents act as agents whose individual decisions are not predictable, we used agent-based modeling to simulate pedestrian movement in order to optimize the spatial distribution of amenities. The digital environment, which allows the parameterization of different types of data, is used for simulation performance. The simulation outcome is quantitatively presented through two criteria of pedestrian accessibility, whose mutual relationship is used to detect the final, optimized combination for the spatial distribution of amenities. This approach can assist with a better understanding of pedestrian dynamics and support pedestrian-friendly choices in urban systems. Finally, the algorithm is applied to the case study of real space in a brownfield location.
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Colombi, A., and M. Scianna. "Modelling human perception processes in pedestrian dynamics: a hybrid approach." Royal Society Open Science 4, no. 3 (March 2017): 160561. http://dx.doi.org/10.1098/rsos.160561.
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In this paper, we present a hybrid mathematical model describing crowd dynamics. More specifically, our approach is based on the well-established Helbing-like discrete model, where each pedestrian is individually represented as a dimensionless point and set to move in order to reach a target destination, with deviations deriving from both physical and social forces. In particular, physical forces account for interpersonal collisions, whereas social components include the individual desire to remain sufficiently far from other walkers (the so-called territorial effect). In this respect, the repulsive behaviour of pedestrians is here set to be different from traditional Helbing-like methods, as it is assumed to be largely determined by how they perceive the presence and the position of neighbouring individuals, i.e. either objectively as pointwise/localized entities or subjectively as spatially distributed masses. The resulting modelling environment is then applied to specific scenarios, that first reproduce a real-world experiment, specifically designed to derive our model hypothesis. Sets of numerical realizations are also run to analyse in more details the pedestrian paths resulting from different types of perception of small groups of static individuals. Finally, analytical investigations formalize and validate from a mathematical point of view selected simulation outcomes.
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Alqurashi, Raghda, and Tom Altman. "Hierarchical Agent-Based Modeling for Improved Traffic Routing." Applied Sciences 9, no. 20 (October 16, 2019): 4376. http://dx.doi.org/10.3390/app9204376.
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Agent-based model (ABM) simulation is a bottom–up approach that can describe the phenomena generated from actions and interactions within a multiagent system. An ABM is an improvement over model simulations which only describe the global behavior of a system. Therefore, it is an appropriate technology to analyze emergent phenomena in social sciences and complex adaptive systems such as vehicular traffic and pedestrian crowds. In this paper, a hybrid agent-based modeling framework designed to automate decision-making processes during traffic congestion is proposed. The model provides drivers with real-time alternative routes, computed via a decentralized multi-agent model, that tries to achieve a system-optimal traffic distribution within an entire system, thus reducing the total travel time of all the drivers. The presented work explores a decentralized ABM technique on an autonomous microgrid that is represented through cellular automata (CA). The proposed model was applied to high-density traffic congestion events such as car accidents or lane closures, and its effectiveness was analyzed. The experimental results confirm the efficiency of the proposed model in not only accurately simulating the driver behaviors and improving vehicular traffic flows during congestion but also by suggesting changes to traffic dynamics during the simulations, such as avoiding obstacles and high-density areas and then selecting the best alternative routes. The simulation results validate the ability of the proposed model and the included decision-making sub-models to both predict and improve the behaviors and intended actions of the agents.
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Lohner, R., Muhammad Baqui, Eberhard Haug, and Britto Muhamad. "Real-time micro-modelling of a million pedestrians." Engineering Computations 33, no. 1 (March 7, 2016): 217–37. http://dx.doi.org/10.1108/ec-02-2015-0036.
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Purpose – The purpose of this paper is to develop a first-principles model for the simulation of pedestrian flows and crowd dynamics capable of computing the movement of a million pedestrians in real-time in order to assess the potential safety hazards and operational performance at events where many individuals are gathered. Examples of such situations are sport and music events, cinemas and theatres, museums, conference centres, places of pilgrimage and worship, street demonstrations, emergency evacuation during natural disasters. Design/methodology/approach – The model is based on a series of forces, such as: will forces (the desire to reach a place at a certain time), pedestrian collision avoidance forces, obstacle/wall avoidance forces; pedestrian contact forces, and obstacle/wall contact forces. In order to allow for general geometries a so-called background triangulation is used to carry all geographic information. At any given time the location of any given pedestrian is updated on this mesh. The model has been validated qualitatively and quantitavely on repeated occasions. The code has been ported to shared and distributed memory parallel machines. Findings – The results obtained show that the stated aim of computing the movement of a million pedestrians in real-time has been achieved. This is an important milestone, as it enables faster-than-real-time simulations of large crowds (stadiums, airports, train and bus stations, concerts) as well as evacuation simulations for whole cities. Research limitations/implications – All models are wrong, but some are useful. The same applies to any modelling of pedestrians. Pedestrians are not machines, so stochastic runs will be required in the future in order to obtain statistically relevant ensembles. Practical implications – This opens the way to link real-time data gathering of crowds (i.e. via cameras) with predictive calculations done faster than real-time, so that security personnel can be alerted to potential future problems during large-scale events. Social implications – This will allow much better predictions for large-scale events, improving security and comfort. Originality/value – This is the first time such speeds have been achieved for a micro-modelling code for pedestrians.
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Alrashed, Mohammed, and Jeff Shamma. "Agent Based Modelling and Simulation of Pedestrian Crowds in Panic Situations." Collective Dynamics 5 (August 12, 2020): A100. http://dx.doi.org/10.17815/cd.2020.100.
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The increasing occurrence of panic stampedes during mass events has motivated studying the impact of panic on crowd dynamics. Understanding the collective behaviors of panic stampedes is essential to reducing the risk of deadly crowd disasters. In this work, we use an agent-based formulation to model the collective human behavior in such crowd dynamics. We investigate the impact of panic behavior on crowd dynamics, as a specific form of collective behavior, by introducing a contagious panic parameter. The proposed model describes the intensity and spread of panic through the crowd. The corresponding panic parameter impacts each individual to represent a different variety of behaviors that can be associated with panic situations such as escaping danger, clustering, and pushing. Simulation results show contagious panic and pushing behavior, resulting in a more realistic crowd dynamics model.
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Hartmann, Dirk, and Peter Hasel. "Efficient Dynamic Floor Field Methods for Microscopic Pedestrian Crowd Simulations." Communications in Computational Physics 16, no. 1 (July 2014): 264–86. http://dx.doi.org/10.4208/cicp.200513.290114a.
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AbstractFloor field methods are one of the most popular medium-scale navigation concepts in microscopic pedestrian simulators. Recently introduced dynamic floor field methods have significantly increased the realism of such simulations, i.e. agreement of spatio-temporal patterns of pedestrian densities in simulations with real world observations. These methods update floor fields continuously taking other pedestrians into account. This implies that computational times are mainly determined by the calculation of floor fields. In this work, we propose a new computational approach for the construction of dynamic floor fields. The approach is based on the one hand on adaptive grid concepts and on the other hand on a directed calculation of floor fields, i.e. the calculation is restricted to the domain of interest. Combining both techniques the computational complexity can be reduced by a factor of 10 as demonstrated by several realistic scenarios. Thus on-line simulations, a requirement of many applications, are possible for moderate realistic scenarios.
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Förster, Nick, Ivan Bratoev, Jakob Fellner, Gerhard Schubert, and Frank Petzold. "Collaborating with the crowd." International Journal of Architectural Computing 20, no. 1 (March 2022): 76–95. http://dx.doi.org/10.1177/14780771221082258.
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Microscopic agent-based simulations promise the meaningful inclusion of crowd dynamics in planning processes. However, such complex urban issues depend on a multiplicity of criteria. Thus, an isolated model cannot represent the walk of pedestrians meaningfully in planning contexts. This paper reframes crowd simulation as collaborative experimentation and embeds it directly in the design process. Beyond the simulation algorithm, this perspective draws attention to user interactions, interfaces, and visualizations as crucial simulation elements. Through a prototype, we combine an agent-based pedestrian simulation with a hybrid physical–digital interface. Based on this configuration, we explore requirements of the early design stages and accordingly discuss concepts for interaction, simulation, and visualization. The prototype blends user inputs with intuitive design interactions, adapts the simulation process to qualitative and dynamic negotiations, and presents results immediately in the discussed context. Thus, it aligns crowd simulation with contingent collaborations and reveals its potential in the early design stages.
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Platt, A., and A. Kneidl. "A Case for Identity Hierarchies in Simulating Social Groups." Collective Dynamics 5 (August 12, 2020): A98. http://dx.doi.org/10.17815/cd.2020.98.
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By considering previous empirical studies in group dynamics, modelling designs for pedestrian simulators and psychological and sociological theories of crowd behaviour, we briefly present a hierarchical, identity-based approach to simulating pedestrian social groups.
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Kleinmeier, Benedikt, Gerta Köster, and John Drury. "Agent-based simulation of collective cooperation: from experiment to model." Journal of The Royal Society Interface 17, no. 171 (October 2020): 20200396. http://dx.doi.org/10.1098/rsif.2020.0396.
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Simulation models of pedestrian dynamics have become an invaluable tool for evacuation planning. Typically, crowds are assumed to stream unidirectionally towards a safe area. Simulated agents avoid collisions through mechanisms that belong to each individual, such as being repelled from each other by imaginary forces. But classic locomotion models fail when collective cooperation is called for, notably when an agent, say a first-aid attendant, needs to forge a path through a densely packed group. We present a controlled experiment to observe what happens when humans pass through a dense static crowd. We formulate and test hypotheses on salient phenomena. We discuss our observations in a psychological framework. We derive a model that incorporates: agents’ perception and cognitive processing of a situation that needs cooperation; selection from a portfolio of behaviours, such as being cooperative; and a suitable action, such as swapping places. Agents’ ability to successfully get through a dense crowd emerges as an effect of the psychological model.
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Elzie, ME, Terra, Erika Frydenlund, MS, Andrew J. Collins, PhD, and R. Michael Robinson, PhD. "Conceptualizing intragroup and intergroup dynamics within a controlled crowd evacuation." Journal of Emergency Management 13, no. 2 (March 1, 2015): 109. http://dx.doi.org/10.5055/jem.2015.0224.
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Social dynamics play a critical role in successful pedestrian evacuations. Crowd modeling research has made progress in capturing the way individual and group dynamics affect evacuations; however, few studies have simultaneously examined how individuals and groups interact with one another during egress. To address this gap, the researchers present a conceptual agent-based model (ABM) designed to study the ways in which autonomous, heterogeneous, decision-making individuals negotiate intragroup and intergroup behavior while exiting a large venue. A key feature of this proposed model is the examination of the dynamics among and between various groupings, where heterogeneity at the individual level dynamically affects group behavior and subsequently group/group interactions. ABM provides a means of representing the important social factors that affect decision making among diverse social groups. Expanding on the 2013 work of Vizzari et al., the researchers focus specifically on social factors and decision making at the individual group and group/group levels to more realistically portray dynamic crowd systems during a pedestrian evacuation. By developing a model with individual, intragroup, and intergroup interactions, the ABM provides a more representative approximation of real-world crowd egress. The simulation will enable more informed planning by disaster managers, emergency planners, and other decision makers. This pedestrian behavioral concept is one piece of a larger simulation model. Future research will build toward an integrated model capturing decision-making interactions between pedestrians and vehicles that affect evacuation outcomes.
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Gasparini, Francesca, Marta Giltri, and Stefania Bandini. "Safety perception and pedestrian dynamics: Experimental results towards affective agents modeling." AI Communications 34, no. 1 (February 15, 2021): 5–19. http://dx.doi.org/10.3233/aic-201576.
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The modeling of a new generation of agent-based simulation systems supporting pedestrian and crowd management taking into account affective states represents a new research frontier. Pedestrian behaviour involves human perception processes, based on subjective and psychological aspects. Following the concept of pedestrian environmental awareness, each walker adapts his/her crossing behaviour according to environmental conditions and his/her perception of safety. Different pedestrian behaviours can be related to subjective mobility and readiness to respond, and these factors are strongly dependent on the subjective interaction with the environment. Having additional inputs about pedestrian behaviour related to their perception processes could be useful in order to develop a more representative pedestrian dynamic model. In particular, the subjective perception of the safeness of crossing should be taken into consideration. In order to focus on the pedestrians’ perception of safe road crossing and walking, an experiment in an uncontrolled urban scenario has been carried out. Besides more conventional self-assessment questionnaires, physiological responses have been considered to evaluate the affective state of pedestrians during the interaction with the urban environment. Results from the analysis of the collected data show that physiological responses are reliable indicators of safety perception while road crossing and interacting with real urban environment, suggesting the design of agent-based models for pedestrian dynamics simulations taking in account the representation of affective states.
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Papelis, YE, RA Kady, LJ Bair, and E. Weisel. "Modeling of human behavior in crowds using a cognitive feedback approach." SIMULATION 93, no. 7 (November 12, 2016): 567–78. http://dx.doi.org/10.1177/0037549716673153.
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We present an agent-based approach to modeling crowd behavior that is based on complementary psychological and engineering principles. The application focus is for developing realistic models that address not only the physical but also the psychological aspects of crowd behavior. Our approach to modeling the psychology of a crowd is based on the principle of emotional reflection. According to this principle, human emotions are evoked in response to the perception of other people’s emotions, implying that emotions propagate in a crowd as a result of each person’s perception of other crowd members’ emotions in addition to external factors. We demonstrate that when incorporating an emotional component into a crowd simulation, there is enough sensitivity between the outcomes and emotion-based responses to provide a rich and powerful test-bed for assessing possible effects of emotionally driven responses in crowds. The emotional model is coupled with a movement model that is based on the social forces formulation, but with parameters that vary according to the current emotional state of each crowd member. We present the model along with results of how different emotional levels can affect the movement dynamics of crowds.
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Stubenschrott, Martin, Thomas Matyus, Helmut Schrom-Feiertag, Christian Kogler, and Stefan Seer. "Route-Choice Modeling for Pedestrian Evacuation Based on Infrastructure Knowledge and Personal Preferences." Transportation Research Record: Journal of the Transportation Research Board 2623, no. 1 (January 2017): 82–89. http://dx.doi.org/10.3141/2623-09.
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In recent years, pedestrian simulation has been a valuable tool for the quantitative assessment of egress performance in various environments during emergency evacuation. For a high level of realism, an evacuation simulation requires a behavioral model that takes into account behavioral aspects of real pedestrians. In many studies, however, it is assumed that simulated pedestrians have a global knowledge of the infrastructure and choose either a predefined or the shortest route. It is questionable whether this simplification provides realistic results. This study addresses the problem of human-like route-choice behavior for microscopic pedestrian simulations. A route-choice model is presented that considers two concepts: first, the modeling of infrastructure knowledge to represent the variations in the decision-making processes of pedestrians with different degrees of familiarity with the infrastructure (e.g., regular commuters versus first-time visitors). Second, for each pedestrian the internal preference for selecting a certain path can be calibrated to allow the choice for the fastest routes or the ones that are most convenient for the agent (e.g., by avoiding stairs). The approach here uses a hybrid route-choice behavior model composed of a graph-based macrolevel representation of the environment, which is augmented with local information to avoid obstacles and dense crowds in the vicinity. This method was applied with different parameter sets in an evacuation study of a multilevel subway station. The results show the impact of these parameters on evacuation times, use of infrastructure elements, and crowd density at specific locations.
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Shirvani, Mohammad, and Georges Kesserwani. "Flood–pedestrian simulator for modelling human response dynamics during flood-induced evacuation: Hillsborough stadium case study." Natural Hazards and Earth System Sciences 21, no. 10 (October 20, 2021): 3175–98. http://dx.doi.org/10.5194/nhess-21-3175-2021.
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Abstract. The flood–pedestrian simulator uses a parallel approach to couple a hydrodynamic model to a pedestrian model in a single agent-based modelling (ABM) framework on graphics processing units (GPU), allowing dynamic exchange and processing of multiple-agent information across the two models. The simulator is enhanced with more realistic human body characteristics and in-model behavioural rules. The new features are implemented in the pedestrian model to factor in age- and gender-related walking speeds for the pedestrians in dry zones around the floodwater and to include a maximum excitement condition. It is also adapted to use age-related moving speeds for pedestrians inside the floodwater, with either a walking condition or a running condition. The walking and running conditions are applicable without and with an existing two-way interaction condition that considers the effects of pedestrian congestion on the floodwater spreading. A new autonomous change of direction condition is proposed to make pedestrian agents autonomous in wayfinding decisions driven by their individual perceptions of the flood risk or the dominant choice made by the others. The relevance of the newly added characteristics and rules is demonstrated by applying the augmented simulator to reproduce a synthetic test case of a flood evacuation in a shopping centre, to then contrast its outcomes against the version of the simulator that does not consider age and gender in the agent characteristics. The enhanced simulator is demonstrated for a real-world case study of a mass evacuation from the Hillsborough football stadium, showing usefulness for flood emergency evacuation planning in outdoor spaces where destination choice and individual risk perception have great influence on the simulation outcomes.
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Zafar, Muzna, Kashif Zia, Dinesh Kumar Saini, Arshad Muhammad, and Alois Ferscha. "Modeling human factors influencing herding during evacuation." International Journal of Pervasive Computing and Communications 13, no. 2 (June 5, 2017): 211–34. http://dx.doi.org/10.1108/ijpcc-03-2017-0024.
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Purpose It has been witnessed that many incidents of crowd evacuation have resulted in catastrophic results, claiming lives of hundreds of people. Most of these incidents were a result of localized herding that eventually turned into global panic. Many crowd evacuation models have been proposed with different aspects of interests. The purpose of this paper is to attempt to bring together many of these aspects to study evacuation dynamics. Design/methodology/approach The proposed agent-based model, in a hypothetical physical environment, uses perception maps for routing decisions which are constructed from agents’ personal observations of the surroundings as well as information gathered through distant communication. Communication is governed by a trust model which measures the authenticity of the information being shared. Agents are of two types; emotional and rational. The trust model is combined with a game-theoretic model to resolve conflict of agents’ own type with that of types of agents in the neighborhood. Findings Evacuation dynamics in different environmental and exit strategies are evaluated on the basis of reduced herding and evacuation time. Using this integrated information sharing model, agents gain an overall view of the environment, sufficient to select the optimal path towards exits with respect to reduced herding and evacuation time. Originality/value The proposed model has been formulated and established using an agent-based simulation integrating important modeling aspects. The paper helps in understanding the interplay between technological and humanistic aspects in smart and pervasive environments.
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Dumitrescu, Catalin, Petrica Ciotirnae, and Constantin Vizitiu. "Fuzzy Logic for Intelligent Control System Using Soft Computing Applications." Sensors 21, no. 8 (April 8, 2021): 2617. http://dx.doi.org/10.3390/s21082617.
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When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.
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Batty, Michael. "Agents, Cells, and Cities: New Representational Models for Simulating Multiscale Urban Dynamics." Environment and Planning A: Economy and Space 37, no. 8 (August 2005): 1373–94. http://dx.doi.org/10.1068/a3784.
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New forms of representation at a fine spatial scale, in which units of space are conceived as cells and populations as individual agents, are currently changing the way we are able to simulate the evolution of cities. In this paper I show how these new approaches are consistent with traditional urban models that have gone before, with the emphasis no longer being on spatial interaction but on development dynamics and local movement. I first introduce ideas about urban simulation based on spatial evolution as reaction and diffusion, showing how problems conceived in terms of cells and/or agents enable new implementations of this generic model. I sketch the rudiments of cellular automata which emphasise rules for development transition, and agent-based models which focus on how individuals respond to environmental attributes encoded in cellular landscapes. I illustrate these exemplars through models of residential location. Three applications are then presented at very different spatial scales: pedestrian movement at the building scale, the evolution of systems of cities at a regional scale, and urban growth at the city scale. I conclude with proposals that formal policy analysis in this domain should always be informed by more than one approach.
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Wang, Guan-ning, Tao Chen, Jin-wei Chen, Kaifeng Deng, and Ru-dong Wang. "Simulation study of crowd dynamics in pedestrian evacuation concerning panic contagion: A cellular automaton approach." Chinese Physics B, January 12, 2022. http://dx.doi.org/10.1088/1674-1056/ac4a66.
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Abstract The study of the panic evacuation process is of great significance to emergency management. Panic not only causes negative emotions such as irritability and anxiety, but also affects the pedestrians decision-making process, thereby inducing the abnormal crowd behavior. Prompted by the epidemiological SIR model, an extended floor field cellular automaton model was proposed to investigate the pedestrian dynamics under the threat of hazard resulting from the panic contagion. In the model, the conception of panic transmission status (PTS) was put forward to describe pedestrians' behavior who could transmit panic emotions to others. The model also indicated the pedestrian movement was governed by the static and hazard threat floor field. Then rules that panic could influence decision-making process were set up based on the floor field theory. The simulation results show that the stronger the pedestrian panic, the more sensitive pedestrians are to hazards, and the less able to rationally find safe exits. However, when the crowd density is high, the panic contagion has a less impact on the evacuation process of pedestrians. It is also found that when the hazard position is closer to the exit, the panic will propagate for a longer time and have a greater impact on the evacuation. The results also suggest that as the extent of pedestrian's familiarity with the environment increases, pedestrians spend less time to escape from the room and are less sensitive to the hazard. In addition, it is essential to point out that, compared with the impact of panic contagion, the pedestrian's familiarity with environment has a more significant influence on the evacuation.
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Bera, Aniket, Sujeong Kim, and Dinesh Manocha. "Modeling Trajectory-level Behaviors using Time Varying Pedestrian Movement Dynamics." Collective Dynamics 3 (May 29, 2018). http://dx.doi.org/10.17815/cd.2018.15.
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We present a novel interactive multi-agent simulation algorithm to model pedestrian movement dynamics. We use statistical techniques to compute the movement patterns and motion dynamics from 2D trajectories extracted from crowd videos. Our formulation extracts the dynamic behavior features of real-world agents and uses them to learn movement characteristics on the fly. The learned behaviors are used to generate plausible trajectories of virtual agents as well as for long-term pedestrian trajectory prediction. Our approach can be integrated with any trajectory extraction method, including manual tracking, sensors, and online tracking methods. We highlight the benefits of our approach on many indoor and outdoor scenarios with noisy, sparsely sampled trajectory in terms of trajectory prediction and data-driven pedestrian simulation.
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Bode, Nikolai. "Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation." Collective Dynamics 5 (March 27, 2020). http://dx.doi.org/10.17815/cd.2020.68.
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Simulation models for pedestrian crowds are a ubiquitous tool in research and industry. It is crucial that the parameters of these models are calibrated carefully and ultimately it will be of interest to compare competing models to decide which model is best suited for a particular purpose. In this contribution, I demonstrate how Approximate Bayesian Computation (ABC), which is already a popular tool in other areas of science, can be used for model fitting and model selection in a pedestrian dynamics context. I fit two different models for pedestrian dynamics to data on a crowd passing in one direction through a bottleneck. One model describes movement in continuous-space, the other model is a cellular automaton and thus describes movement in discrete-space. In addition, I compare models to data using two metrics. The first is based on egress times and the second on the velocity of pedestrians in front of the bottleneck. My results show that while model fitting is successful, a substantial degree of uncertainty about the value of some model parameters remains after model fitting. Importantly, the choice of metric in model fitting can influence parameter estimates. Model selection is inconclusive for the egress time metric but supports the continuous-space model for the velocity-based metric. These findings show that ABC is a flexible approach and highlights the difficulties associated with model fitting and model selection for pedestrian dynamics. ABC requires many simulation runs and choosing appropriate metrics for comparing data to simulations requires careful attention. Despite this, I suggest ABC is a promising tool, because it is versatile and easily implemented for the growing number of openly available crowd simulators and data sets.
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Nappi, Manuela Marques Lalane, Ivana Righetto Moser, and João Carlos Souza. "Influence of different merging angles of pedestrian flows on evacuation time." Fire Research 3, no. 1 (October 11, 2019). http://dx.doi.org/10.4081/fire.2019.75.
Full textAbstract:
The growing number of fires and other types of catastrophes occurring at large events highlights the need to rethink safety concepts and also to include new ways to optimize buildings and venues where events are held. Although there have been some attempts to model and simulate the movement of pedestrian crowds, little knowledge has been gathered to better understand the impact of the built environment and its geometric characteristics on the crowd dynamics. This paper presents computer simulations about pedestrians’ crowd dynamics that were conducted based on the Social Force Model. The influence of different configurations of pedestrian flows merging during emergency evacuations was investigated. In this study, 12 designs with different merging angles were examined, simulating the evacuation of 400 people in each scenario. The Planung Transport Verkehr (PTV, German for Planning Transport Traffic) Viswalk module of the PTV Vissim software (PTV Group, Karlsruhe, Germany) program was adopted, which allows the employment of the Social Force approach. The results demonstrate that both symmetric and asymmetric scenarios are sensitive to the angles of convergence between pedestrian flows.
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Hesham, Omar, and Gabriel Wainer. "Advanced models for centroidal particle dynamics: short-range collision avoidance in dense crowds." SIMULATION, April 16, 2021, 003754972110031. http://dx.doi.org/10.1177/00375497211003126.
Full textAbstract:
Computer simulation of dense crowds is finding increased use in event planning, congestion prediction, and threat assessment. State-of-the-art particle-based crowd methods assume and aim for collision-free trajectories. That is an idealistic yet not overly realistic expectation, as near-collisions increase in dense and rushed settings compared with typically sparse pedestrian scenarios. Centroidal particle dynamics (CPD) is a method we defined that explicitly models the compressible personal space area surrounding each entity to inform its local pathing and collision-avoidance decisions. We illustrate how our proposed agent-based method for local dynamics can reproduce several key emergent dense crowd phenomena at the microscopic level with higher congruence to real trajectory data and with more visually convincing collision-avoidance paths than the existing state of the art. We present advanced models in which we consider distraction of the pedestrians in the crowd, flocking behavior, interaction with vehicles (ambulances, police) and other advanced models that show that emergent behavior in the simulated crowds is similar to the behavior observed in reality. We discuss how to increase confidence in CPD, potentially making it also suitable for use in safety-critical applications, including urban design, evacuation analysis, and crowd-safety planning.
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Wu, Yanru, Junxin Li, and Qing Sun. "Study on human-induced vibration of a cable-stayed bridge without backstays located in abrupt valley." Advances in Structural Engineering, May 30, 2021, 136943322110203. http://dx.doi.org/10.1177/13694332211020397.
Full textAbstract:
This research aims to assess the pedestrian comfort and to control human-induced vibration of an arch tower cable-stayed bridge without backstays located in canyon. Dynamic simulations of human-induced vibration were carried out with a mode-by-mode approach, and the results indicated that a total of seven lateral and vertical modes of the bridge may suffer from excessive vibrations at the design crowd density. Based on the periodic walking force, the structure response under pedestrian loads was evaluated performing dynamic analyses with two Finite Element models of the footbridge. A single tuned mass damper (STMD) control system was developed for control of human-induced vibration, which consisted of four tuned mass dampers mounted on the mid-span of bridge to enhance damping ratios of lively modes. The results indicate that the maximum acceleration for the first-order lateral and second-order vertical vibration at the design crowd density exceed the associated threshold values referring to the comfort level 1 (CL1) Criteria. The critical pedestrian number of lateral dynamic instability estimated by the Dallard’s empirical formula is much smaller than the dynamic design pedestrian number; and the Dallard’s empirical formula is applicable to estimate the critical pedestrian number of lateral dynamic instability for this bridge by comparing with Pedroe Inês footbridge. The damping ratios for both the vertical and lateral modes increase appreciably after installing the tuned mass dampers and no evidence of large-amplitude vibrations has been observed, leading to the realization of satisfactory comfort levels, which can provide reference for vibration reduction design of this kind of bridge.
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Jia, Xiaolu, Claudio Feliciani, Daichi Yanagisawa, and Katsuhiro Nishinari. "Experimental study on the evading behaviour of single pedestrians encountering an obstacle." Collective Dynamics 5 (March 27, 2020). http://dx.doi.org/10.17815/cd.2020.36.
Full textAbstract:
Present simulation and experimental research still have deficiency in depicting the evading behaviour of single pedestrians confronting with an obstacle, which is the basis for the study of crowd dynamics affected by obstacles in real life. Therefore, this study will conduct experiments with a bar-shaped obstacle in the middle of a corridor and explore the corresponding general and particular features of single pedestrians. Particularly, the variation of pedestrian velocity and trajectory under different-sized obstacles will be illustrated. By taking the average velocity and trajectories of the 32 participants, it could be concluded that pedestrians would walk at a velocity of about 1.5 m/s without being affected by the size of obstacle. Besides, pedestrians tend to pass a location about 0.4 meters away from the obstacle edge that is perpendicular to walking direction. Furthermore, pedestrians tend to begin and finish evading the obstacle at locations respectively about 4.40 meters and 4.85 meters away from the obstacle. We also found a heterogeneity in the evading behaviour and pedestrians could be classified into four types accordingly. Results of this study are expected to provide reliable evidence for agent-based modelling in the future.
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Gu, Zongchao, Sunhao Su, Wei Lu, and Yishu Yao. "Estimating Spatiotemporal Contacts Between Individuals in Underground Shopping Streets Based on Multi-Agent Simulation." Frontiers in Physics 10 (May 13, 2022). http://dx.doi.org/10.3389/fphy.2022.882904.
Full textAbstract:
Coronavirus disease 2019 (COVID-19) has exposed the public safety issues. Obtaining inter-individual contact and transmission in the underground spaces is an important issue for simulating and mitigating the spread of the pandemic. Taking the underground shopping streets as an example, this study aimed to verify commercial facilities’ influence on the spatiotemporal distribution of inter-individual contact in the underground space. Based on actual surveillance data, machine learning techniques are adopted to obtain utilizers’ dynamics in underground pedestrian system and shops. Firstly, an entropy maximization approach is adopted to estimate pedestrians’ origin-destination (OD) information. Commercial utilization behaviors at different shops are modeled based on utilizers’ entering frequency and staying duration, which are obtained by re-identifying individuals’ disappearances and appearances at storefronts. Based on observed results, a simulation method is proposed to estimate utilizers’ spatiotemporal contact by recreating their space-time paths in the underground system. Inter-individual contact events and exposure duration are obtained in view of their space-time vectors in passages and shops. A social contact network is established to describe the contact relations between all individuals in the whole system. The exposure duration and weighted clustering coefficients were defined as indicators to measure the contact degree of individual and the social contact network. The simulation results show that the individual and contact graph indicators are similar across time, while the spatial distribution of inter-individual contact within shops and passages are time-varying. Through simulation experiments, the study verified the effects of self-protection and commercial type adjustment measures.