Academic literature on the topic 'Pedestrian dynamics, crowd, agent-based approach, simulation'
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Journal articles on the topic "Pedestrian dynamics, crowd, agent-based approach, simulation"
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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.
Dissertations / Theses on the topic "Pedestrian dynamics, crowd, agent-based approach, simulation"
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MANENTI, LORENZA ALESSANDRA. "Agent-based proxemic dynamics: crowd and groups simulation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/42374.
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Considering the general overview on the Pedestrian Dynamics area, this thesis is focused in the area of pedestrian dynamics simulation, with the goal to study the phenomenon of groups as constitutive elements that compose a crowd, analyzing if their presence influences the dynamics of pedestrian flow and evaluating the impact of their contribution.
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Alrashed, Mohammed. "Control Theoretic Approaches to Computational Modeling and Risk Mitigation for Large Crowd Management." Diss., 2020. http://hdl.handle.net/10754/665965.
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We develop a computational framework for risk mitigation in high population density events. With increased global population, the frequency of high population density events is naturally increased. Therefore, risk-free crowd management plans are critical for efficient mobility, convenient daily life, resource management and most importantly mitigation of any inadvertent incidents and accidents such as stampedes. The status-quo for crowd management plans is the use of human experience/expert advice. However, most often such dependency on human experience is insufficient, flawed and results in inconvenience and tragic events. Motivated by these issues, we propose an agent-based mathematical model describing realistic human motion and simulating large dense crowds in a wide variety of events as a potential simulation testbed to trial crowd management plans. The developed model incorporates stylized mindset characteristics as an internal drive for physical behavior such as walking, running, and pushing. Furthermore, the model is combined with a visualisation of crowd movement. We develop analytic tools to quantify crowd dynamic features. The analytic tools will enable verification and validation to empirical evidence and surveillance video feed in both local and holistic representations of the crowd. This work addresses research problems in computational modeling of crowd dynamics, specifically: understanding and modeling the impact of a collective mindset on crowd dynamics versus mixtures of heterogeneous mindsets, the effect of social contagion of behaviors and decisions within the crowd, the competitive and aggressive pushing behaviors, and torso and steering dynamics.
Book chapters on the topic "Pedestrian dynamics, crowd, agent-based approach, simulation"
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Schadschneider, Andreas, Hubert Klüpfel, Tobias Kretz, Christian Rogsch, and Armin Seyfried. "Fundamentals of Pedestrian and Evacuation Dynamics." In Multi-Agent Systems for Traffic and Transportation Engineering, 124–54. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-226-8.ch006.
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Multi-Agent Simulation is a general and powerful framework for understanding and predicting the behaviour of social systems. Here the authors investigate the behaviour of pedestrians and human crowds, especially their physical movement. Their aim is to build a bridge between the multi-agent and pedestrian dynamics communities that facilitates the validation and calibration of modelling approaches which is essential for any application in sensitive areas like safety analysis. Understanding the dynamical properties of large crowds is of obvious practical importance. Emergency situations require efficient evacuation strategies to avoid casualties and reduce the number of injured persons. In many cases legal requirements have to be fulfilled, for example, for aircraft or cruise ships. For tests already in the planning stage reliable simulation models are required to avoid additional costs for changes in the construction. First, the empirically observed phenomena are described, emphasizing the challenges they pose for any modelling approach and their relevance for the validation and calibration. Then the authors review the basic modelling approaches used for the simulation of pedestrian dynamics in normal and emergency situations, focussing on cellular automata models. Their achievements as well as their limitations are discussed in view of the empirical results. Finally, two applications to safety analysis are briefly described.
Conference papers on the topic "Pedestrian dynamics, crowd, agent-based approach, simulation"
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Qiu Qin and Junhu Wei. "An agent-based approach for crowd dynamics simulation." In 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icicisys.2010.5658843.
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