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Relevant bibliographies by topics / Crowd, Pedestrian, Proxemics, Simulation / Journal articles

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Journal articles on the topic 'Crowd, Pedestrian, Proxemics, Simulation'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Li, Jun, and Haoxiang Zhang. "Crowd Evacuation Simulation Research Based on Improved Reciprocal Velocity Obstacles (RVO) Model with Path Planning and Emotion Contagion." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 3 (2021): 740–57. http://dx.doi.org/10.1177/03611981211056910.

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Crowd evacuation simulation is an important research topic for designing reasonable building layout and effective evacuation routes. The reciprocal velocity obstacles (RVO) model is a pedestrian motion model which is used, but it does not work when complex and multiple obstacles are present in the scene. This paper proposes an improved RVO model with path planning and emotion contagion for crowd evacuation simulation. The model uses the vertices of the obstacles to construct pedestrian path nodes for planning pedestrian evacuation paths. To make the pedestrian evacuation paths simulation resul

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Sarmady, Siamak, Fazilah Haron, and Abdullah Zawawi Talib. "Simulation of pedestrian movements using a fine grid cellular automata model." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (2022): 1197. http://dx.doi.org/10.11591/ijai.v11.i4.pp1197-1212.

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Crowd simulation is used in evacuation and crowd safety inspections and in the study of the performance of crowd systems and animations. Cellular automata are extensively utilized in crowd modeling. In regular cellular automata models, each pedestrian occupies a single cell with the size of a pedestrian body. The movements of pedestrians resemble those of chess pieces on a chessboard because the space is divided into relatively large cells. Furthermore, all pedestrians feature the same body size and speed. This study proposes a fine grid cellular automata model that uses small cells and allows

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Siamak, Sarmady, Haron Fazilah, and Zawawi Talib Abdullah. "Simulation of pedestrian movements using a fine grid cellular automata model." International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (2022): 1197–212. https://doi.org/10.11591/ijai.v11.i4.pp1197-1212.

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Crowd simulation is used in evacuation and crowd safety inspections and in the study of the performance of crowd systems and animations. Cellular automata are extensively utilized in crowd modeling. In regular cellular automata models, each pedestrian occupies a single cell with the size of a pedestrian body. The movements of pedestrians resemble those of chess pieces on a chessboard because the space is divided into relatively large cells. Furthermore, all pedestrians feature the same body size and speed. This study proposes a fine grid cellular automata model that uses small cells and allows

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4

Li, Cuiling, Rongyong Zhao, Chuanfeng Han, Rahman Arifur, Yunlong Ma, and Qiong Liu. "Dynamic Disturbance Propagation Model of Pedestrian Panic Behaviors and Lyapunov-Based Crowd Stability Analysis." Applied Sciences 13, no. 21 (2023): 11762. http://dx.doi.org/10.3390/app132111762.

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In public places, pedestrian panic behaviors have received increasing attention due to their dangerous impact on normal pedestrian flow. To address this issue, this study considered crowd panic behaviors as two-dimensional Gaussian disturbances quantitatively triggered by accidents and analyzed the stability of the pedestrian crowd based on Lyapunov criterion. First, this study established a two-dimensional static model for the disturbance pressure in a crowd. Then, a dynamic disturbance–propagation model (DPM) of crowd panic behaviors was proposed based on the conservation law of fluid dynami

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Zanlungo, Francesco, Zeynep Yucel, Claudio Feliciani, Katsuhiro Nishinari, and Takayuki Kanda. "Congestion Number Analysis of Cross-Flow Dynamics: Experimental Data and Simulations." Collective Dynamics 9 (May 17, 2024): 1–8. http://dx.doi.org/10.17815/cd.2024.153.

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We recently proposed the "Congestion Number" (CN) as a metricto evaluate the state of a pedestrian crowd. Such metric, whose definition is based on the gradient of the rotor of the crowd velocity field, appears to provide additional information with respect to traditional metrics based on pedestrian density and flow. We also published two works on the dynamics of orthogonally crossing pedestrian flows under different density regimes. In the first manuscript we analysed experimental data by using traditionalobservables such as density, velocity and relative position between pedestrians, along w

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Vizzari, Giuseppe, and Thomas Cecconello. "Pedestrian Simulation with Reinforcement Learning: A Curriculum-Based Approach." Future Internet 15, no. 1 (2022): 12. http://dx.doi.org/10.3390/fi15010012.

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Pedestrian simulation is a consolidated but still lively area of research. State of the art models mostly take an agent-based perspective, in which pedestrian decisions are made according to a manually defined model. Reinforcement learning (RL), on the other hand, is used to train an agent situated in an environment how to act so as to maximize an accumulated numerical reward signal (a feedback provided by the environment to every chosen action). We explored the possibility of applying RL to pedestrian simulation. We carefully defined a reward function combining elements related to goal orient

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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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Qiu, Fasheng, and Xiaolin Hu. "Modeling group structures in pedestrian crowd simulation." Simulation Modelling Practice and Theory 18, no. 2 (2010): 190–205. http://dx.doi.org/10.1016/j.simpat.2009.10.005.

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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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Liu, Yuanyuan, and Toshiyuki Kaneda. "Using agent-based simulation for public space design based on the Shanghai Bund waterfront crowd disaster." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 34, no. 2 (2020): 176–90. http://dx.doi.org/10.1017/s0890060420000049.

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AbstractWith growing city density and mass gatherings held all over the world in urban spaces, crowd disasters have been happening each year. In considering the avoidance of crowd disasters and the reduction of fatalities, it is important to analyze the efficient spatial layout of the public space in situations of high crowd density. Compared with traditional empirical design methods, computational approaches have better abilities for quantitative analysis and are gradually being adopted in the planning and management of the urban public space. In this paper, we investigated the official docum

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11

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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12

Jin, Lianghai, Mei Fang, Shu Chen, Wenfan Lei, and Yun Chen. "Tangential Change Behavior and Pedestrian Simulation of Multichannel Evacuation Crowd." Mathematical Problems in Engineering 2020 (October 21, 2020): 1–13. http://dx.doi.org/10.1155/2020/7649094.

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In evacuation, the velocity difference of adjacent pedestrians before and after often leads to tangential change of pedestrian location in channel. This tangential change behavior and its interaction disturb the stable state of crowd evacuation in multiple channels, which can affect the efficiency of crowd evacuation and even cause trampling accidents. This paper considers the dynamic comfort distance and the expected speed and analyzes the relative position changes after pedestrians change lanes. It investigates the conditions of tangential change behavior and defines the rules of tangential

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13

Usher, John M., Eric Kolstad, and Xuan Liu. "Simulation of Pedestrian Behavior in Intermodal Facilities." International Journal of Agent Technologies and Systems 2, no. 3 (2010): 66–82. http://dx.doi.org/10.4018/jats.2010070105.

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Planning pedestrian environments requires that designers understand how pedestrians interact with their environment and one another. With improved knowledge, the design and planning of pedestrian areas can provide improvements in safety, throughput, and utility. This paper provides an overview of the Intermodal Simulator for the Analysis of Pedestrian Traffic (ISAPT). It focuses on the methodologies used in simulation of the pedestrian traffic, including route planning and navigation. Several illustrations of the system’s ability to reproduce observed crowd behavior are provided.

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Muhammed, Danial A., Tarik A. Rashid, Abeer Alsadoon, et al. "An Improved Simulation Model for Pedestrian Crowd Evacuation." Mathematics 8, no. 12 (2020): 2171. http://dx.doi.org/10.3390/math8122171.

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This paper works on one of the most recent pedestrian crowd evacuation models—i.e., “a simulation model for pedestrian crowd evacuation based on various AI techniques”—which was developed in late 2019. This study adds a new feature to the developed model by proposing a new method and integrating it into the model. This method enables the developed model to find a more appropriate evacuation area design regarding safety due to selecting the best exit door location among many suggested locations. This method is completely dependent on the selected model’s output—i.e., the evacuation time for eac

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Qiu, Fasheng, and Xiaolin Hu. "Spatial activity-based modeling for pedestrian crowd simulation." SIMULATION 89, no. 4 (2012): 451–65. http://dx.doi.org/10.1177/0037549711435950.

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Liao, Can, Kejun Zhu, Haixiang Guo, and Jian Tang. "Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium." Complexity 2019 (January 15, 2019): 1–15. http://dx.doi.org/10.1155/2019/7942483.

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Current research on pedestrian flows has mainly focused on evacuation optimization during or after emergencies; however, crowd management before emergencies has received little attention. This paper examines the management of a Safe Pedestrian Flow Rate, in which the Bayesian-Nash Equilibrium mimics pedestrians’ decision-making, and a multiagent system is employed to reproduce pedestrians’ interactions. In the model, the pedestrian tunnel is divided into cells, with each pedestrian in a cell receiving a utility depending on the distance to the exit and the number of pedestrians in the cell. Th

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Wang, Hao, and Muzhou Xiong. "Towards modeling pedestrian’s invisible trail for simulating crowd movement." International Journal of Modeling, Simulation, and Scientific Computing 09, no. 02 (2018): 1850016. http://dx.doi.org/10.1142/s1793962318500162.

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Crowd modeling and simulation have drawn much attention in recent decades due to the functionality of recurrence of the crowd movement pattern in an efficient way. Much effort has been paid aiming at generating an accurate simulation result with respect to different aspects of crowd movement pattern. A fact has been observed that footprint left in mud or turf significantly affects pedestrian’s decision making and moving trajectory since those footprints help other pedestrians walk comfortably. Inspired by this, we in this paper propose a crowd simulation model aiming to model how the movement

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18

Hu, Qu Qiang, and Zhi Gang Song. "Modeling and Simulation on Unidirectional Pedestrian Flow Based on Cellular Automata." Applied Mechanics and Materials 482 (December 2013): 350–54. http://dx.doi.org/10.4028/www.scientific.net/amm.482.350.

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The CA-based Model of unidirectional pedestrian flow simulation is established. Model takes into account pedestrian forward, change lanes , side forward, backward , away from the dense crowd behavior. Simulation research and analyzed the relationship between pedestrian flow speed ,flow speed, flow , without moving the proportion of pedestrians and the pedestrian density in different pedestrian density. The results showed that: unidirectional pedestrian flow with the pedestrian density increases, there will be two thresholds K1 and K2. Pedestrian flow velocity will appear slight and obvious dec

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19

Aleksandrov, Mitko, David J. Heslop, and Sisi Zlatanova. "3D Indoor Environment Abstraction for Crowd Simulations in Complex Buildings." Buildings 11, no. 10 (2021): 445. http://dx.doi.org/10.3390/buildings11100445.

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This paper presents an approach for the automatic abstraction of built environments needed for pedestrian dynamics from any building configuration. The approach assesses the usability of navigation mesh to perform realistically pedestrian simulation considering the physical structure and pedestrian abilities for it. Several steps are examined including the creation of a navigation mesh, space subdivision, border extraction, height map identification, stairs classification and parametrisation, as well as pedestrian simulation. A social-force model is utilised to simulate the interactions betwee

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20

Wu, Wenhan, Wenfeng Yi, Xiaolu Wang, and Xiaoping Zheng. "A force-based model for adaptively controlling the spatial configuration of pedestrian subgroups at non-extreme densities." Transportation Research Part C: Emerging Technologies 152 (May 11, 2023): 104154. https://doi.org/10.1016/j.trc.2023.104154.

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The study of crowd dynamics has provided new insights into the understanding of human collective motion. However, most previous studies treated large-scale crowds as consisting of isolated individuals, but ignored the fact that pedestrian subgroups are prevalent in reality. With the increasing advancement of computer simulations, the critical role of subgroups in crowd modeling has been gradually recognized. Here, we develop a force-based model to reproduce the walking behaviors of pedestrian subgroups, in which the quantitative laws extracted from public datasets are incorporated for controll

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21

Gödel, Marion, Rainer Fischer, and Gerta Köster. "Sensitivity Analysis for Microscopic Crowd Simulation." Algorithms 13, no. 7 (2020): 162. http://dx.doi.org/10.3390/a13070162.

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Microscopic crowd simulation can help to enhance the safety of pedestrians in situations that range from museum visits to music festivals. To obtain a useful prediction, the input parameters must be chosen carefully. In many cases, a lack of knowledge or limited measurement accuracy add uncertainty to the input. In addition, for meaningful parameter studies, we first need to identify the most influential parameters of our parametric computer models. The field of uncertainty quantification offers standardized and fully automatized methods that we believe to be beneficial for pedestrian dynamics

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22

Togashi, Fumiya, Takashi Misaka, Rainald Löhner, and Shigeru Obayashi. "Using ensemble Kalman filter to determine parameters for computational crowd dynamics simulations." Engineering Computations 35, no. 7 (2018): 2612–28. http://dx.doi.org/10.1108/ec-03-2018-0115.

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Purpose It is of paramount importance to ensure safe and fast evacuation routes in cities in case of natural disasters, environmental accidents or acts of terrorism. The same applies to large-scale events such as concerts, sport events and religious pilgrimages as airports and to traffic hubs such as airports and train stations. The prediction of pedestrian is notoriously difficult because it varies depending on circumstances (age group, cultural characteristics, etc.). In this study, the Ensemble Kalman Filter (EnKF) data assimilation technique, which uses the updated observation data to impr

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23

Yang, Shuo, Jianrong Yang, and Rui Li. "Evaluation of Pedestrian Comfort for a Footbridge with Hinged Piers." Sustainability 15, no. 13 (2023): 9851. http://dx.doi.org/10.3390/su15139851.

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To study the standardized evaluation method of vibration comfort of pedestrian bridges, the effect of the transient response term is ignored based on the generalized single degree of freedom (SDOF) method with reference to the American Institution of Steel Construction inc (AISC 11) specification. The resonance conditions between the crowd and the bridge structure are also considered, and the pedestrian bridge structure is simplified to an SDOF system. Then, the peak acceleration of the structure under crowd excitation is directly calculated using the generalized crowd load, and the comfort ev

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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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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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COLOMBO, RINALDO M., MAURO GARAVELLO, and MAGALI LÉCUREUX-MERCIER. "A CLASS OF NONLOCAL MODELS FOR PEDESTRIAN TRAFFIC." Mathematical Models and Methods in Applied Sciences 22, no. 04 (2012): 1150023. http://dx.doi.org/10.1142/s0218202511500230.

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We present a new class of macroscopic models for pedestrian flows. Each individual is assumed to move towards a fixed target, deviating from the best path according to the instantaneous crowd distribution. The resulting equation is a conservation law with a nonlocal flux. Each equation in this class generates a Lipschitz semigroup of solutions and is stable with respect to the functions and parameters defining it. Moreover, key qualitative properties such as the boundedness of the crowd density are proved. Specific models are presented and their qualitative properties are shown through numeric

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27

Huang, Peng, and Zhen Liu. "A Model of Pedestrian Crowd Behavior for Evacuation Simulation." Advanced Science Letters 7, no. 1 (2012): 404–7. http://dx.doi.org/10.1166/asl.2012.2723.

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28

Seitz, Michael J., Felix Dietrich, and Gerta Köster. "A Study of Pedestrian Stepping Behaviour for Crowd Simulation." Transportation Research Procedia 2 (2014): 282–90. http://dx.doi.org/10.1016/j.trpro.2014.09.054.

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29

Hu, QingMei, WeiNing Fang, YuQuan Jia, and Ye Deng. "The simulation and analysis of pedestrian crowd and behavior." Science in China Series E: Technological Sciences 52, no. 6 (2008): 1762–67. http://dx.doi.org/10.1007/s11431-008-0211-9.

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30

Paris, Sébastien, Julien Pettré, and Stéphane Donikian. "Pedestrian Reactive Navigation for Crowd Simulation: a Predictive Approach." Computer Graphics Forum 26, no. 3 (2007): 665–74. http://dx.doi.org/10.1111/j.1467-8659.2007.01090.x.

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31

Abdul Salam, Parveena Shamim, Wolfgang Bock, Axel Klar, and Sudarshan Tiwari. "Disease contagion models coupled to crowd motion and mesh-free simulation." Mathematical Models and Methods in Applied Sciences 31, no. 06 (2021): 1277–95. http://dx.doi.org/10.1142/s0218202521400066.

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Modeling and simulation of disease spreading in pedestrian crowds have recently become a topic of increasing relevance. In this paper, we consider the influence of the crowd motion in a complex dynamical environment on the course of infection of the pedestrians. To model the pedestrian dynamics, we consider a kinetic equation for multi-group pedestrian flow based on a social force model coupled with an Eikonal equation. This model is coupled with a non-local SEIS contagion model for disease spread, where besides the description of local contacts, the influence of contact times has also been mo

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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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33

Li, De Wei, and Bao Ming Han. "Modeling Queue Service System in Pedestrian Simulation." Advanced Materials Research 187 (February 2011): 1–6. http://dx.doi.org/10.4028/www.scientific.net/amr.187.1.

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Pedestrian simulation is widely used on the assessment of facility design and crowd safety control. It proposed a grid-based model of queue simulation system considering human physiology and psychology. Both logic queue system and animation queue system are modeled separately. Deadlock deal mechanism is designed. The proposed model established a good interface between the pedestrian behavior, queue system and animation. It can reproduce phenomenon like traffic shock wave effectively. A case study is shown by simulation of ticket vendor machine layout assessment in Beijing South Railway Station

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Papadimitriou, E., J. M. Auberlet, G. Yannis, and S. Lassarre. "Simulation of Pedestrians and Motorised Traffic." International Journal of Interdisciplinary Telecommunications and Networking 6, no. 1 (2014): 57–73. http://dx.doi.org/10.4018/ijitn.2014010105.

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The objective of this paper is the analysis of the state of the art in pedestrian simulation models and the identification of key issues for further research, with particular focus on the modelling of pedestrians and motorised traffic. A review and a comparative assessment of pedestrian simulation models are carried out, including macroscopic models, earlier meso- and miscosimulation models (mostly in Cellular Automata) and more recent Multi-Agent simulation models. The reviewed models cover a broad range of research topics: pedestrian flow and level of service, crowd dynamics and evacuations,

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Shibiao, Mu, and Chen Zhijun. "Crowd evacuation model based on bacterial foraging algorithm." International Journal of Modern Physics C 29, no. 03 (2018): 1850027. http://dx.doi.org/10.1142/s0129183118500274.

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To understand crowd evacuation, a model based on a bacterial foraging algorithm (BFA) is proposed in this paper. Considering dynamic and static factors, the probability of pedestrian movement is established using cellular automata. In addition, given walking and queue times, a target optimization function is built. At the same time, a BFA is used to optimize the objective function. Finally, through real and simulation experiments, the relationship between the parameters of evacuation time, exit width, pedestrian density, and average evacuation speed is analyzed. The results show that the model

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Ma, Yaping, Xiaoying Liu, Feizhou Huo, and Hui Li. "Analysis of Cooperation Behaviors and Crowd Dynamics during Pedestrian Evacuation with Group Existence." Sustainability 14, no. 9 (2022): 5278. http://dx.doi.org/10.3390/su14095278.

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At most public places where large-scale events are held, the crowd as a pedestrian particle system is a mixture of individuals and groups rather than a pure collection of individuals. The interaction behaviors of pedestrians within the same group and between different groups are significantly disparate, which makes the crowd evacuation process more complex. To address this issue, a new pedestrian evacuation model is proposed incorporating the cellular automaton model and game theory. In the model, two game theory models named prisoner’s dilemma and harmony game are applied to depict the intera

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Li, Ming Hua, Zhen Zhou Yuan, and Yan Xu. "Applied Technology in a Developed Simulation Model of Pedestrian Crowd Dynamics during Emergency Evacuation." Advanced Materials Research 1022 (August 2014): 223–28. http://dx.doi.org/10.4028/www.scientific.net/amr.1022.223.

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In this paper, we present a developed cellular automata model to simulate the pedestrians’ crowd behaviors in congested public facility during emergency evacuation. Pedestrian perception and choice behavior considering the queue time of door changing were investigated in pedestrian decision and evacuation time. The model was used to mimic the emergency evacuation with a range of densities for the study of relationship between individual behavior and evacuation time. The results indicate that pedestrian is sensitively for the queue time and prefer to change the exit if the evacuation time perce

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Yan, Dapeng, Gangyi Ding, Kexiang Huang, Chongzhi Bai, Lian He, and Longfei Zhang. "Enhanced Crowd Dynamics Simulation with Deep Learning and Improved Social Force Model." Electronics 13, no. 5 (2024): 934. http://dx.doi.org/10.3390/electronics13050934.

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The traditional social force model (SFM) in crowd simulation experiences difficulty coping with the complexity of the crowd, limited by singular physical formulas and parameters. Recent attempts to combine deep learning with these models focus more on simulating specific states of crowds. This paper introduces an advanced deep social force model, influenced by crowd states. It utilizes deep neural networks to accurately fit crowd trajectory features, enhancing behavior simulation capabilities. Geometrical constraints within the model provide control over varied crowd behaviors, adjustable to s

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Luo, Wei, Yi Wang, Pengpeng Jiao, and Zehao Wang. "Improvement Strategy at Pedestrian Bottleneck in Subway Stations." Discrete Dynamics in Nature and Society 2022 (September 23, 2022): 1–12. http://dx.doi.org/10.1155/2022/7258907.

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The bottleneck normally refers to a narrowed region that decreases the flow, which is the key limiting factor in the pedestrian flow in the subway station. Due to the confined space, pedestrians are frequently forced to gather together at bottlenecks, which could not only limit the pedestrians’ efficiency and comfort but also cause serious crowd catastrophes such as stampedes. Optimization techniques for crowd congestion in subway stations should be investigated. This study proposed and demonstrated a set of optimization methods using conduction field experiments. The effects of passing time,

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Chen, Hongyi, Jingtao Ding, Yong Li, Yue Wang, and Xiao-Ping Zhang. "Social Physics Informed Diffusion Model for Crowd Simulation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 1 (2024): 474–82. http://dx.doi.org/10.1609/aaai.v38i1.27802.

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Crowd simulation holds crucial applications in various domains, such as urban planning, architectural design, and traffic arrangement. In recent years, physics-informed machine learning methods have achieved state-of-the-art performance in crowd simulation but fail to model the heterogeneity and multi-modality of human movement comprehensively. In this paper, we propose a social physics-informed diffusion model named SPDiff to mitigate the above gap. SPDiff takes both the interactive and historical information of crowds in the current timeframe to reverse the diffusion process, thereby generat

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Li, Zhihong, Shiyao Qiu, Xiaoyu Wang, and Li Zhao. "Modeling and Simulation of Crowd Pre-Evacuation Decision-Making in Complex Traffic Environments." International Journal of Environmental Research and Public Health 19, no. 24 (2022): 16664. http://dx.doi.org/10.3390/ijerph192416664.

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Human movements in complex traffic environments have been successfully simulated by various models. It is crucial to improve crowd safety and urban resilience. However, few studies focus on reproducing human behavior and predicting escape reaction time in the initial judgement stage in complex traffic environments. In this paper, a pedestrian pre-evacuation decision-making model considering pedestrian heterogeneity is proposed for complex environments. Firstly, the model takes different obvious factors into account, including cognition, information, experience, habits, stress, and decision-mak

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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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Yue-wen, Fu, Li Meng, Liang Jia-hong, and Hu Xiao-qian. "Optimal Acceleration-Velocity-Bounded Trajectory Planning in Dynamic Crowd Simulation." Journal of Applied Mathematics 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/501689.

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Creating complex and realistic crowd behaviors, such as pedestrian navigation behavior with dynamic obstacles, is a difficult and time consuming task. In this paper, we study one special type of crowd which is composed of urgent individuals, normal individuals, and normal groups. We use three steps to construct the crowd simulation in dynamic environment. The first one is that the urgent individuals move forward along a given path around dynamic obstacles and other crowd members. An optimal acceleration-velocity-bounded trajectory planning method is utilized to model their behaviors, which ens

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Zhu, Kongjin, Jun Wang, Ning Guo, Zhongjun Ding, and Peng Mei. "Simulation of pedestrian counter flow with conflicting preference using a lattice-based simulation model." International Journal of Modern Physics C 31, no. 09 (2020): 2050120. http://dx.doi.org/10.1142/s012918312050120x.

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Pedestrian counter flows widely exist in public pedestrian facilities such as corridors, sidewalks, signalized crossings and so on. There is one specific flow in real life, namely counter flow with conflicting walking preference which often occurs in the case of presence of one-sidedly asymmetry due to shadows, light, snow and so on. It is often overlooked in practice and the related studies are still limited. In this study, to better understand the flow dynamics of pedestrian flow with various walking preference, a simple lattice-based model was proposed in which position exchange and walking

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Chen, Tan, Wei Wang, Yu Tu, and Xuedong Hua. "Modelling Unidirectional Crowd Motion in a Corridor with Statistical Characteristics of Pedestrian Movements." Mathematical Problems in Engineering 2020 (June 30, 2020): 1–11. http://dx.doi.org/10.1155/2020/7483210.

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Lattice gas model is a kind of mature and convenient pedestrian simulation model. The original lattice gas model adopts discontinuous step length and finite moving directions to simulate crowd motion, which will lead to some unreasonable movements; besides, the transition probability used in this model is often manually designed and lacks the verification of realistic pedestrian trajectories. Based on an open pedestrian trajectory dataset, we first derived the relationship between local density and the distribution of pedestrian movements’ length and then proposed an extended lattice gas model

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Sung, Mankyu, and SeongKi Kim. "Crowd Simulation with Arrival Time Constraints." Symmetry 12, no. 11 (2020): 1804. http://dx.doi.org/10.3390/sym12111804.

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Finding collision-free paths for crowd simulation has been a core technique in video games and the film industry; it has drawn a great deal of attention from computer animation researchers for several decades. Additionally, theoretical modeling of pedestrian has been a hot topic in physics as well because it allows us to predict any architectural failure of buildings and many city planning problems. However, the existing studies for path planning cannot guarantee the arrival order, which is critical in many cases, such as arrival symmetry of the characters within video games or films. To resol

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Wang, Yiyu, Jiaqi Ge, and Alexis Comber. "Simulation model of pedestrian flow based on multi-agent system and Bayesian Nash equilibrium." AGILE: GIScience Series 2 (June 4, 2021): 1–7. http://dx.doi.org/10.5194/agile-giss-2-42-2021.

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Abstract. Computer-based simulation is a means of exploring complex systems and has become the mainstream method of pedestrian research. In this research, a multi-agent simulation model of pedestrian flow will be established using a multi-agent system (MAS) and Bayesian Nash equilibrium. MAS is used to simulate the crowd movement and the interaction between pedestrians, and Bayesian Nash equilibrium is adopted to analyze the decision-making process of pedestrians. In contrast to previous pedestrian flow simulation modeling methods, this study adopts multi-agent modeling to realize the complete

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Shi, Xiaomeng, Zhirui Ye, Nirajan Shiwakoti, and Offer Grembek. "A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement." Journal of Advanced Transportation 2018 (September 2, 2018): 1–42. http://dx.doi.org/10.1155/2018/1063043.

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Complex movement patterns of pedestrian traffic, ranging from unidirectional to multidirectional flows, are frequently observed in major public infrastructure such as transport hubs. These multidirectional movements can result in increased number of conflicts, thereby influencing the mobility and safety of pedestrian facilities. Therefore, empirical data collection on pedestrians’ complex movement has been on the rise in the past two decades. Although there are several reviews of mathematical simulation models for pedestrian traffic in the existing literature, a detailed review examining the c

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Hu, Jun, Zhongwen Li, Lei You, Hong Zhang, Juan Wei, and Mei Li. "Simulation of queuing time in crowd evacuation by discrete time loss queuing method." International Journal of Modern Physics C 30, no. 08 (2019): 1950057. http://dx.doi.org/10.1142/s0129183119500578.

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We have proposed a new evacuation model based on discrete time loss queuing method in order to effectively depict the queuing of pedestrians in an indoor space and its effect over evacuation performance. In this model, the calculation formula of pedestrian movement probability is given first based on field value and average queuing time; the average queuing time is depicted with the discrete time loss queuing method and the adopted evacuation strategy is set forth through defining cellular evolution process. Moreover, with the use of the established simulation platform for experiment, we have

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Bao, Yushun. "The Effect of Herding Behavior on the Efficiency of Pedestrian Evacuation in Subway Stations." Scientific and Social Research 6, no. 5 (2024): 105–11. http://dx.doi.org/10.26689/ssr.v6i5.6897.

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In the emergency evacuation of pedestrians in subway stations, most people do not know the correct evacuation routes and methods, and tend to follow others blindly, resulting in herding behavior. To study the process of pedestrian evacuation with herding behavior in subway stations, a cellular automata pedestrian evacuation model is established to simulate the pedestrian evacuation with herding behavior in subway stations, and the effects of the weight coefficients of the parameters in the model on the overall evacuation time and the distribution of people’s positions are investigated to quant

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