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Bibliographies thématiques / Pedestrian dynamics, crowd, agent-based approach, simulation / Articles de revues

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Articles de revues sur le sujet « Pedestrian dynamics, crowd, agent-based approach, simulation »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 31 juillet 2025

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1

Hayashida, Tomohiro, Shinya Sekizaki, Yushi Furuya, and Ichiro Nishizaki. "ACS2-Powered Pedestrian Flow Simulation for Crowd Dynamics." AppliedMath 5, no. 3 (2025): 88. https://doi.org/10.3390/appliedmath5030088.

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Pedestrian flow simulations play a pivotal role in urban planning, transportation engineering, and disaster response by enabling the detailed analysis of crowd dynamics and walking behavior. While physical models such as the Social Force model and Boids have been widely used, they often struggle to replicate complex inter-agent interactions. On the other hand, reinforcement learning (RL) methods, although adaptive, suffer from limited interpretability due to their opaque policy structures. To address these limitations, this study proposes a pedestrian simulation framework based on the Anticipa

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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 (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 interac

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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 (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

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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 (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 s

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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 (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 Economic

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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 th

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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 (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 rep

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Alqurashi, Raghda, and Tom Altman. "Hierarchical Agent-Based Modeling for Improved Traffic Routing." Applied Sciences 9, no. 20 (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 wi

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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 (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

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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 corresp

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Yasufuku, Kensuke, and Akira Takahashi. "Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management." Journal of Disaster Research 19, no. 2 (2024): 248–55. http://dx.doi.org/10.20965/jdr.2024.p0248.

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Crowd management at large-scale events and specific facilities is a critical issue from the perspectives of safety and service quality improvement. Traditional methods for crowd management often rely on empirical knowledge, which has limitations in quickly grasping the on-site situation and making decisions on the spot. In this study, we developed a real-time crowd flow prediction and visualization platform incorporating an agent-based crowd simulation and an advanced crowd management system called crowd management platform as a service. In a case study focused on the area around the Tokyo Dom

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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 (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 constru

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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 (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 ped

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Senasinghe, Asiri P., Willem Klumpenhouwer, Ahmed Labidi, and Lina Kattan. "An Agent-Based Crowd Dynamics Simulation that Considers Idling and Time-and-Distance-Conscious Optimising Behaviour." Journal of South Asian Logistics and Transport 4, no. 1 (2024): 119–44. http://dx.doi.org/10.4038/jsalt.v4i1.90.

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This agent-based simulation study investigates pedestrian dynamics with a focus on the impacts of behaviour idling on pedestrian flows. It also examines the influence of psychological, social, and environmental factors on pedestrian flows. Our research categorises pedestrian behaviour into three types: time-sensitive (Type A), mobility-constrained (Type B), and 'wandering' type (Type C), defined as pedestrians moving without a specific destination, which includes tourists, shoppers, and leisure walkers. We demonstrate how behaviour heterogeneity influences flow and movement patterns through si

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Kiyama, Masato, Motoki Amagasaki, and Toshiaki Okamoto. "Multi-Agent Reinforcement Learning-Based Control Method for Pedestrian Guidance Using the Mojiko Fireworks Festival Dataset." Electronics 14, no. 6 (2025): 1062. https://doi.org/10.3390/electronics14061062.

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With increasing incidents due to congestion at events, effective pedestrian guidance has become a critical safety concern. Recent research has explored the application of reinforcement learning to crowd simulation, where agents learn optimal actions through trial and error to maximize rewards based on environmental states. This study investigates the use of reinforcement learning and simulation techniques to mitigate pedestrian congestion through improved guidance systems. We employ the Multi-Agent Deep Deterministic Policy Gradient (MA-DDPG), a multi-agent reinforcement learning approach, and

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Nicolas, Alexandre, and Simon Mendez. "Viral Transmission in Pedestrian Crowds: Coupling an Open-source Code Assessing the Risks of Airborne Contagion with Diverse Pedestrian Dynamics Models." Collective Dynamics 9 (June 20, 2024): 1–10. http://dx.doi.org/10.17815/cd.2024.159.

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We study viral transmission in crowds via the short-ranged airborne pathway using a purely model-based approach. Our goal is two-pronged. Firstly, we illustrate with a concrete and pedagogical case study how to estimate the risks of new viral infections by coupling pedestrian simulations with the transmission algorithm that we recently released as open-source code. The algorithm hinges on pre-computed viral concentration maps derived from computational fluid dynamics (CFD) simulations. Secondly, we investigate to what extent the transmission risk predictions depend on the pedestrian dynamics m

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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 (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

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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 (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 exa

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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 (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 depend

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Locatelli, M., L. Pellegrini, D. Accardo, E. Sulis, L. C. Tagliabue, and G. M. Di Giuda. "People flow management in a healthcare facility through crowd simulation and agent-based modeling methods." Journal of Physics: Conference Series 2600, no. 14 (2023): 142007. http://dx.doi.org/10.1088/1742-6596/2600/14/142007.

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Abstract The study investigates the optimization of user flow and space management in a hospital located in Turin by simulating activities and patient flows of the blood drawing center. The simulation aims to verify the maximum number of people allowed to occupy the spaces simultaneously, manage user flows, and verify compliance with COVID-19 pandemic restrictions. Pedestrian Dynamics, supported by Building Information Modeling (BIM) methods, and NetLogo are used to simulate and optimize user flow and space management relying on crowd simulation and Agent-Based Modeling. Patients’ movements an

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Dang, Huu-Tu, Benoit Gaudou, and Nicolas Verstaevel. "HyPedSim: A Multi-Level Crowd-Simulation Framework—Methodology, Calibration, and Validation." Sensors 24, no. 5 (2024): 1639. http://dx.doi.org/10.3390/s24051639.

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Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based model to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a us

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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 (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 membe

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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 (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

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Tordeux, Antoine, and Claudia Totzeck. "Multi-scale description of pedestrian collective dynamics with port-Hamiltonian systems." Networks and Heterogeneous Media 18, no. 2 (2023): 906–29. http://dx.doi.org/10.3934/nhm.2023039.

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<abstract><p>Port-Hamiltonian systems (PHS) theory is a recent but already well-established modelling approach for non-linear physical systems. Some studies have shown lately that PHS frameworks are relevant for modelling and control of swarm and multi-agent systems. We identify in this contribution a general class of microscopic force-based pedestrian models that can be formulated as a port-Hamiltonian system. The pedestrian PHS has linear structure and dissipation components. Non-linear effects come from isotropic pedestrian interactions. Simulation results on a torus with disord

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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 (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 excitem

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López, Baeza Jesús, Jose Carpio-Pinedo, Julia Sievert, et al. "Modeling Pedestrian Flows: Agent-Based Simulations of Pedestrian Activity for Land Use Distributions in Urban Developments." Sustainability 13, no. 16 (2021): 9268. https://doi.org/10.3390/su13169268.

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Pedestrian activity is a cornerstone for urban sustainability, with key implications for the environment, public health, social cohesion, and the local economy. Therefore, city planners, urban designers, and decision-makers require tools to predict pedestrian mobility and assess the walkability of existing or planned urban environments. For this purpose, diverse approaches have been used to analyze different inputs such as the street network configuration, density, land use mix, and the location of certain amenities. This paper focuses on the location of urban amenities as key elements for ped

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Zhang, Deyin, Gang Liu, Kaifa Kang, et al. "Quantifying Thermal Demand in Public Space: A Pedestrian-Weighted Model for Outdoor Thermal Comfort Design." Buildings 15, no. 13 (2025): 2156. https://doi.org/10.3390/buildings15132156.

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With accelerating urbanization, the outdoor thermal environment has become a critical factor affecting the thermal comfort of public spaces, particularly in high-density commercial districts and pedestrian-concentrated areas. To enhance thermal comfort and livability in public outdoor space, this study proposes a thermal demand-responsive design approach that integrates thermal conditions with pedestrian flow dynamics. A commercial pedestrian mall featuring semi-open public spaces and air-conditioned interior retail areas was selected as a case study. Computational Fluid Dynamics (CFD) simulat

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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 (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 cons

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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 (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

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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 (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

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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

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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 manua

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Wang, Yiyu, Jiaqi Ge, and Alexis Comber. "Modelling emergent pedestrian evacuation behaviors from intelligent, game-playing agents." Journal of Computational Social Science 8, no. 2 (2025). https://doi.org/10.1007/s42001-025-00369-9.

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Abstract Much work has been done to understand complex crowd dynamics and self-organizing behaviors in high-density crowd situations. But most approaches for modelling pedestrian dynamics in emergencies require complex computations, making it difficult to capture multiple individual behaviors within a single model. This paper describes an agent-based model (ABM) that incorporates Bayesian game theory into pedestrian simulations. It assumes that players (agents) are playing a Bayesian game (i.e. games with incomplete information) and adopt strategies based on the anticipated behaviors of others

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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

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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 (2019). http://dx.doi.org/10.4081/fire.2019.75.

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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 influ

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Ding, Ning, Zhenyu Fan, Xiaopeng Zhu, Shancheng Lin, and Yang Wang. "Multi-agent modeling of crowd dynamics under bombing attack cases." Frontiers in Physics 11 (January 10, 2024). http://dx.doi.org/10.3389/fphy.2023.1200927.

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Terrorist attacks are a catastrophic man-made emergent phenomenon. The current situation of international violent terrorism is severe. Public places with high-density crowds are more likely to be attacked by violent terrorists. To effectively reduce the number of casualties caused by violent terrorist incidents, it is crucial to take preventive management at the beginning of the incident. This paper analyzed the characteristics of the self-organization of crowds and terrorists in public places during a suicide bombing attack and conducted simulation experiments with an agent-based model. The s

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Zhang, Yong, Bo Yang, and Jianlin Zhu. "A double‐layer crowd evacuation simulation method based on deep reinforcement learning." Computer Animation and Virtual Worlds 35, no. 3 (2024). http://dx.doi.org/10.1002/cav.2280.

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AbstractExisting crowd evacuation simulation methods commonly face challenges of low efficiency in path planning and insufficient realism in pedestrian movement during the evacuation process. In this study, we propose a novel crowd evacuation path planning approach based on the learning curve–deep deterministic policy gradient (LC‐DDPG) algorithm. The algorithm incorporates dynamic experience pool and a priority experience sampling strategy, enhancing convergence speed and achieving higher average rewards, thus efficiently enabling global path planning. Building upon this foundation, we introd

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Suchak, Keiran, Minh Kieu, Yannick Oswald, Jonathan A. Ward, and Nick Malleson. "Coupling an agent-based model and an ensemble Kalman filter for real-time crowd modelling." Royal Society Open Science 11, no. 4 (2024). http://dx.doi.org/10.1098/rsos.231553.

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Agent-based modelling has emerged as a powerful tool for modelling systems that are driven by discrete, heterogeneous individuals and has proven particularly popular in the realm of pedestrian simulation. However, real-time agent-based simulations face the challenge that they will diverge from the real system over time. This paper addresses this challenge by integrating the ensemble Kalman filter (EnKF) with an agent-based crowd model to enhance its accuracy in real time. Using the example of Grand Central Station in New York, we demonstrate how our approach can update the state of an agent-ba

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Zhang, Feiyang, Becky P. Y. Loo, and Chang Jiang. "Behavioural changes in open space during COVID-19 with deep learning-based video analytics." Proceedings of the Institution of Civil Engineers - Municipal Engineer, September 8, 2023, 1–30. http://dx.doi.org/10.1680/jmuen.23.00020.

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While numerous studies have been done to examine the general trend of urban mobility during COVID-19, there is not enough research on changes in pedestrian behavioural characteristics and crowd dynamics in public space. Understanding and monitoring such changes are critical for the better management and design of public open space in case of future outbreaks of infectious diseases. To fill this gap, pedestrian movements are tracked and analysed with deep learning-based video analytics based on anonymized video footage along a major promenade in Hong Kong before and during COVID-19. Specificall

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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.

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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 il

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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.

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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 tu

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Li, Ruowei, Farah Ghizzawi, Tho V. Le, and Matthew J. Roorda. "Behavior of a Person-Following Robot in Pedestrian Environments: Laboratory Experimentation and Simulation." Transportation Research Record: Journal of the Transportation Research Board, April 30, 2025. https://doi.org/10.1177/03611981251332248.

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As e-commerce continues to grow, the demand for fast and efficient last-mile delivery is increasing. Person-following robots is a solution that is now beginning to be deployed to assist foot couriers in performing last-mile delivery tasks in public areas, such as underground pedestrian walkways and malls. Although they have proved their capacity to operate successfully in uncrowded and highly regulated spaces like warehouses, it is still uncertain whether their performance would be satisfactory in crowded, unstructured, and complex environments. This study proposes a simulation approach for ev

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Negi, Rajendra Singh, Priyanka Iyer, and Gerhard Gompper. "Controlling inter-particle distances in crowds of motile, cognitive, active particles." Scientific Reports 14, no. 1 (2024). http://dx.doi.org/10.1038/s41598-024-59022-6.

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AbstractDistance control in many-particle systems is a fundamental problem in nature. This becomes particularly relevant in systems of active agents, which can sense their environment and react by adjusting their direction of motion. We employ agent-based simulations to investigate the complex interplay between agent activity, characterized by Péclet number $$\hbox{Pe}$$ Pe , reorientation maneuverability $$\Omega$$ Ω , vision angle $$\theta$$ θ and vision range $$R_0$$ R 0 , and agent density, which determines agent distancing and dynamics. We focus on semi-dense crowds, where the vision rang

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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.

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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 th

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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.

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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 ent

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Matthews, Justin Robert, and Angelique Nairn. "The Actotron." M/C Journal 27, no. 6 (2024). http://dx.doi.org/10.5204/mcj.3118.

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Introduction – The Advent of the Actotron Imagine a movie production where leading actors are not bound by human limitations, and digital entities render every emotion, movement, and line with breathtaking precision. This is no longer a conceptual idea but is becoming more possible with the increased integration of artificial intelligence (AI) into screen production activities. Essentially, we are at the dawn of the Actotron era. These advanced virtual actors, equipped with artificial intelligence, could transform not just how movies are made, but who makes them and what stories they tell. The

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