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Journal articles on the topic 'Pedestrian crowds'
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1
Zhang, Dawei, Haitao Zhu, Shi Qiu, and Boyan Wang. "Characterization of Collision Avoidance in Pedestrian Crowds." Mathematical Problems in Engineering 2019 (March 28, 2019): 1–9. http://dx.doi.org/10.1155/2019/9237674.
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The avoidance behavior of pedestrians was characterized in the present paper by simulating the movement of crowds in both unidirectional and bidirectional pedestrian flow. A phase change of alternative lane formation observed in real bidirectional pedestrian flows has been studied, where pedestrians tended to evade individuals in counterflow and simultaneously keep a certain distance from each other in the uniform pedestrian flow when the counterflow disappeared. What is more, the comparison between the effect of evading and pushing behavior on evacuation has been investigated in the room egress scenario. Additionally, the evading and overtaking behavior of fast pedestrians have also been simulated in heterogeneous crowds. The performance of the proposed model was compared to the experimental data and the results obtained using other evacuation models. Numerical results showed that both the phase change of alternative lane formation in bidirectional pedestrian flow and the effective evading behavior in unidirectional pedestrian flow were conductive to reduce the evacuation time of pedestrian crowds. Even though pushing behavior of fast pedestrians seemed to improve the flow through the wide exit, it might lead to the panic and other negative effect on the crowds, such as crowds trample. The proposed model in this paper could provide a theoretical basis for the pedestrian crowd management during emergency evacuation.
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Appert-Rolland, Cécile, Julien Pettré, Anne-Hélène Olivier, William Warren, Aymeric Duigou-Majumdar, Etienne Pinsard, and Alexandre Nicolas. "Experimental Study of Collective Pedestrian Dynamics." Collective Dynamics 5 (September 11, 2020): A109. http://dx.doi.org/10.17815/cd.2020.109.
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We report on two series of experiments, conducted in the frame of two different collaborations designed to study how pedestrians adapt their trajectories and velocities in groups or crowds. Strong emphasis is put on the motivations for the chosen protocols and the experimental implementation. The first series deals with pattern formation, interactions between pedestrians, and decision-making in pedestrian groups at low to medium densities. In particular, we show how pedestrians adapt their headways in single-file motion depending on the (prescribed) leader’s velocity. The second series of experiments focuses on static crowds at higher densities, a situation that can be critical in real life and in which the pedestrians’ choices of motion are strongly constrained sterically. More precisely, we study the crowd’s response to its crossing by a pedestrian or a cylindrical obstacle of 74cm in diameter. In the latter case, for a moderately dense crowd, we observe displacements that quickly decay with the minimal distance to the obstacle, over a lengthscale of the order of the meter.
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Li, Maoyu, Zhizuan Zhou, Ping Zhang, Nan Jiang, Xinmiao Jia, Xiaoyu Ju, and Lizhong Yang. "Effect of walking height on movement of individuals and crowds in a corridor." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 8 (August 1, 2023): 083403. http://dx.doi.org/10.1088/1742-5468/aceb59.
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Abstract The safe and efficient evacuation of pedestrians in an emergency has been widely investigated in the past. Stooping is a common walking posture of pedestrians in evacuation. Understanding the basic laws of pedestrian movement with stoop posture is instructive for developing effective evacuation management in an emergency. However, the evacuation behaviors and movement characteristics of stooped pedestrians are still unclear. In this study, a series of experiments on individuals and crowds with different walking heights were conducted in an 18 m long corridor. It was found that a left-deflection phenomenon appears in the transition from upright walking to stooped walking, and the deflection angles of pedestrians decrease with increasing walking height. The influence of walking height on pedestrian velocity is revealed through the comparison of individual and crowd movement. Restricted walking height can promote the movement velocity of individuals at low speed levels, and weakens the velocity at high speed levels. In contrast to the individual, the velocities of crowds at different speed levels will be enhanced by restricted walking height. Generally, pedestrian movement is affected by the initial motivation, walking height and pedestrian density. Restricted walking height has an encouraging effect in the motivation of pedestrian movement but can increase the physical discomfort of pedestrians. Besides, crowd density has an inhibitory effect on pedestrian movement, and restricted walking height can alleviate high crowd density, implying that appropriate stoop movement can facilitate pedestrian traffic and evacuation to some extent.
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Templeton, Anne, John Drury, and Andrew Philippides. "Walking together: behavioural signatures of psychological crowds." Royal Society Open Science 5, no. 7 (July 2018): 180172. http://dx.doi.org/10.1098/rsos.180172.
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Research in crowd psychology has demonstrated key differences between the behaviour of physical crowds where members are in the same place at the same time, and the collective behaviour of psychological crowds where the entire crowd perceive themselves to be part of the same group through a shared social identity. As yet, no research has investigated the behavioural effects that a shared social identity has on crowd movement at a pedestrian level. To investigate the direction and extent to which social identity influences the movement of crowds, 280 trajectories were tracked as participants walked in one of two conditions: (1) a psychological crowd primed to share a social identity; (2) a naturally occurring physical crowd. Behaviour was compared both within and between the conditions. In comparison to the physical crowd, members of the psychological crowd (i) walked slower, (ii) walked further, and (iii) maintained closer proximity. In addition, pedestrians who had to manoeuvre around the psychological crowd behaved differently to pedestrians who had to manoeuvre past the naturally occurring crowd. We conclude that the behavioural differences between physical and psychological crowds must be taken into account when considering crowd behaviour in event safety management and computer models of crowds.
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Bellomo, Nicola, and Livio Gibelli. "Toward a mathematical theory of behavioral-social dynamics for pedestrian crowds." Mathematical Models and Methods in Applied Sciences 25, no. 13 (September 17, 2015): 2417–37. http://dx.doi.org/10.1142/s0218202515400138.
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This paper presents a new approach to behavioral-social dynamics for pedestrian crowds by suitable development of mathematical tools of the kinetic theory. It is shown how pedestrians heterogeneity and the propagation of local unusual behaviors in the crowd can be accounted for. The proposed model is applied to the study of two groups of pedestrians walking in opposite directions in a crowded street and its predictive ability is demonstrated by showing that emerging behaviors, such as pedestrian segregation, can be depicted.
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Qiu, Fasheng, and Xiaolin Hu. "A Framework for Modeling Social Groups in Agent-Based Pedestrian Crowd Simulations." International Journal of Agent Technologies and Systems 4, no. 1 (January 2012): 39–58. http://dx.doi.org/10.4018/jats.2012010103.
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Grouping is a common phenomenon in pedestrian crowds and social groups can have significant impacts on crowd behavior. Despite its importance, how to model social groups in pedestrian crowd simulations is still an open and challenging issue. This paper presents a framework for modeling social groups in agent-based pedestrian crowd simulations. The developed framework integrates agent behavior modeling, group modeling, and social context modeling in a layered architecture, where each layer focuses on modeling a specific aspect of pedestrian crowds. A model of dynamic grouping behavior is developed to demonstrate the utility of the developed framework, and experimental results are presented.
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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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da Silva, Felipe Tavares, Halane Maria Braga Fernandes Brito, and Roberto Leal Pimentel. "Modeling of crowd load in vertical direction using biodynamic model for pedestrians crossing footbridges." Canadian Journal of Civil Engineering 40, no. 12 (December 2013): 1196–204. http://dx.doi.org/10.1139/cjce-2011-0587.
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In the analysis of vibration of footbridges in vertical direction, for crowd situations, there is evidence in the literature that the whole effect of pedestrian action is not well modeled when applying current force-only models to represent such an action. In these models, the action of each pedestrian is represented by a pulsating force applied on the structure. In this paper, a crowd load model is proposed for sparse and dense crowds (with densities up to around 1.0 pedestrian/m2) in which biodynamic models are added to represent the whole action of pedestrians. The focus of the investigation is on vibration effects in vertical direction. Comparisons with measurements on a prototype footbridge were carried out and made it possible to identify differences in the structural response when applying force-only and force-biodynamic models to represent the pedestrian action. The latter (proposed) model resulted in a better agreement with the measurements.
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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. Then, each pedestrian uses the Bayesian-Nash Equilibrium to search for the target cell with maximum expected utility, moves in, and makes next decision until exiting the tunnel. The simulation model is calibrated and validated from a real scenario. Finally, from the experimental data collected from different simulation scenarios, this research reaches the conclusion that the Safe Pedestrian Flow Rate increases by about 2.96ped/s as the tunnel width expanded by 1m. This paper offers a novel method for reducing potential losses caused by crowd emergencies and can be a valuable reference for managing pedestrian flows and designing public places.
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R, Shaamili. "A Research Perceptive on Deep Learning Framework for Pedestrian Detection in a Crowd." Computational Intelligence and Machine Learning 3, no. 2 (October 14, 2022): 9–14. http://dx.doi.org/10.36647/ciml/03.02.a002.
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In populated cities, we often find crowded events like political meetings, religious festivals, music concerts, and events in shopping malls, which have more safety issues. Smart surveillance systems are used in big cities to keep crowds safe and make crowd security less complicated and more accurate. However, the surveillance systems proposed for a crowd are monitored by human agents, which are inefficient, error-prone, and overwhelming. Even with deep learning-based feature engineering in crowds, many variants of crowd analysis still lack attention and are technically unaddressed. Considering this scenario, the smart system requires the most advanced techniques to monitor the security of the crowd. Crowd analysis is commonly divided into crowd statics and behavior analysis. This paper explores more about crowd behaviour analysis, pedestrian and group detection which describes the movements that are noticed in the crowd image. Subsequently, the issues of the current methodology of pedestrian detection, datasets, and evaluation criteria are analyzed. Keyword : Crowd Analysis, Pedestrian and group detection, deep learning, Crowd IoT analysis, Human Activity Recognition.
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Duives, Dorine C., Winnie Daamen, and Serge P. Hoogendoorn. "Operational Walking Dynamics of Crowds Modeled with Linear Regression." Transportation Research Record: Journal of the Transportation Research Board 2623, no. 1 (January 2017): 90–97. http://dx.doi.org/10.3141/2623-10.
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In this study the influence of interaction characteristics on operational walking dynamics within a crowd—specifically the influence of the distance headway, time headway, angle of sight, angle of interaction, walking speed, and number of pedestrians located nearby on a pedestrian’s change in speed and direction—is investigated. To the authors’ best knowledge, this is the first time that the combined effect of the characteristics of interactions between pedestrians on the operational walking dynamics of pedestrians has been quantified. The walking speed and the number of pedestrians in close proximity were found to influence the adaptation of speed and direction. The other characteristics of the interaction affect either the change in speed (i.e., distance headway and interaction angle) or the change in direction (i.e., time headway and angle of sight). The results of this study strongly indicate that the density experienced by pedestrians is not the only characteristic of the crowd that affects pedestrians’ operational walking dynamics. Consequently, to model crowd movements correctly, the other characteristics of the interaction must also be taken into account in pedestrian flow theory and simulation models.
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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 (April 9, 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 modeled. Hydrodynamic approximations of the coupled system are derived. Finally, simulations of the hydrodynamic model are carried out using a mesh-free particle method. Different numerical test cases are investigated, including uni- and bi-directional flow in a passage with and without obstacles.
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Zhao, Pengfei, Lishan Sun, Liya Yao, Li Cui, and Kaili Zhang. "Analysis of Impact of Group Walking Patterns on Pedestrian Evacuation." Transportation Research Record: Journal of the Transportation Research Board 2604, no. 1 (January 2017): 71–81. http://dx.doi.org/10.3141/2604-09.
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An understanding of the walking patterns of groups of pedestrians in an evacuation is critical for the establishment of policies, procedures, and organizational structures to respond effectively to emergencies. Groups of pedestrians compose a crowd in which pedestrian motions are significantly constrained to maintain cohesion. On the basis of behavior theory, this paper proposes a multiagent model for the simulation of crowds of pedestrians. The main innovative aspect of this model is the genuine representation of the patterns of movement of groups of pedestrians. Patterns of movement consisting of the line-abreast pattern, the chain pattern, and the mixed pattern were investigated, and their influences on evacuations were evaluated quantitatively by taking into account the discrepant densities, disparate distributions of the proportions of pedestrian groups of different sizes, and heterogeneous velocities of groups of pedestrians. The simulation results show that the walking patterns of groups of pedestrians have a significant influence on the dynamics of pedestrian evacuation. The chain pattern was safer when the time of evacuation under high-density conditions was considered, and the mixed pattern had a better performance under moderate-density conditions. Moreover, the influence of patterns of movement was distinct with different distributions of pedestrian groups of different sizes; the chain pattern had the highest evacuation efficiency among the three patterns of pedestrian movement. In addition, a homogeneous velocity condition had a higher evacuation efficiency than a heterogeneous velocity condition. Thus, a chain pattern with a homogeneous velocity is recommended as the optimal pattern of movement in pedestrian evacuations when the safety and efficiency of plans and designs for the evacuation of pedestrian traffic with the different patterns of movement are considered.
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JOHANSSON, ANDERS, DIRK HELBING, HABIB Z. AL-ABIDEEN, and SALIM AL-BOSTA. "FROM CROWD DYNAMICS TO CROWD SAFETY: A VIDEO-BASED ANALYSIS." Advances in Complex Systems 11, no. 04 (August 2008): 497–527. http://dx.doi.org/10.1142/s0219525908001854.
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The study of crowd dynamics is interesting because of the various self-organization phenomena resulting from the interactions of many pedestrians, which may improve or obstruct their flow. Besides formation of lanes of uniform walking direction and oscillations at bottlenecks at moderate densities, it was recently discovered that stop-and-go waves [D. Helbing et al., Phys. Rev. Lett.97 (2006) 168001] and a phenomenon called "crowd turbulence" can occur at high pedestrian densities [D. Helbing et al., Phys. Rev. E75 (2007) 046109]. Although the behavior of pedestrian crowds under extreme conditions is decisive for the safety of crowds during the access to or egress from mass events as well as for situations of emergency evacuation, there is still a lack of empirical studies of extreme crowding. Therefore, this paper discusses how one may study high-density conditions based on suitable video data. This is illustrated at the example of pilgrim flows entering the previous Jamarat Bridge in Mina, 5 kilometers from the Holy Mosque in Makkah, Saudi-Arabia. Our results reveal previously unexpected pattern formation phenomena and show that the average individual speed does not go to zero even at local densities of 10 persons per square meter. Since the maximum density and flow are different from measurements in other countries, this has implications for the capacity assessment and dimensioning of facilities for mass events. When conditions become congested, the flow drops significantly, which can cause stop-and-go waves and a further increase of the density until critical crowd conditions are reached. Then, "crowd turbulence" sets in, which may trigger crowd disasters. For this reason, it is important to operate pedestrian facilities sufficiently below their maximum capacity and to take measures to improve crowd safety, some of which are discussed in the end.
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Liu, Menghang, Luning Li, Qiang Li, Yu Bai, and Cheng Hu. "Pedestrian Flow Prediction in Open Public Places Using Graph Convolutional Network." ISPRS International Journal of Geo-Information 10, no. 7 (July 2, 2021): 455. http://dx.doi.org/10.3390/ijgi10070455.
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Open public places, such as pedestrian streets, parks, and squares, are vulnerable when the pedestrians thronged into the sidewalks. The crowd count changes dynamically over time with various external factors, such as surroundings, weekends, and peak hours, so it is essential to predict the accurate and timely crowd count. To address this issue, this study introduces graph convolutional network (GCN), a network-based model, to predict the crowd flow in a walking street. Compared with other grid-based methods, the model is capable of directly processing road network graphs. Experiments show the GCN model and its extension STGCN consistently and significantly outperform other five baseline models, namely HA, ARIMA, SVM, CNN and LSTM, in terms of RMSE, MAE and R2. Considering the computation efficiency, the standard GCN model was selected to predict the crowd. The results showed that the model obtains superior performances with higher prediction precision on weekends and peak hours, of which R2 are above 0.9, indicating the GCN model can capture the pedestrian features in the road network effectively, especially during the periods with massive crowds. The results will provide practical references for city managers to alleviate road congestion and help pedestrians make smarter planning and save travel time.
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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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Rio, Kevin W., Gregory C. Dachner, and William H. Warren. "Local interactions underlying collective motion in human crowds." Proceedings of the Royal Society B: Biological Sciences 285, no. 1878 (May 16, 2018): 20180611. http://dx.doi.org/10.1098/rspb.2018.0611.
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It is commonly believed that global patterns of motion in flocks, schools and crowds emerge from local interactions between individuals, through a process of self-organization. The key to explaining such collective behaviour thus lies in deciphering these local interactions. We take an experiment-driven approach to modelling collective motion in human crowds. Previously, we observed that a pedestrian aligns their velocity vector (speed and heading direction) with that of a neighbour. Here we investigate the neighbourhood of interaction in a crowd: which neighbours influence a pedestrian's behaviour, how this depends on neighbour position, and how the influences of multiple neighbours are combined. In three experiments, a participant walked in a virtual crowd whose speed and heading were manipulated. We find that neighbour influence is linearly combined and decreases with distance, but not with lateral position (eccentricity). We model the neighbourhood as (i) a circularly symmetric region with (ii) a weighted average of neighbours, (iii) a uni-directional influence, and (iv) weights that decay exponentially to zero by 5 m. The model reproduces the experimental data and predicts individual trajectories in observational data on a human ‘swarm’. The results yield the first bottom-up model of collective crowd motion.
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Bain, Nicolas, and Denis Bartolo. "Dynamic response and hydrodynamics of polarized crowds." Science 363, no. 6422 (January 3, 2019): 46–49. http://dx.doi.org/10.1126/science.aat9891.
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Modeling crowd motion is central to situations as diverse as risk prevention in mass events and visual effects rendering in the motion picture industry. The difficulty of performing quantitative measurements in model experiments has limited our ability to model pedestrian flows. We use tens of thousands of road-race participants in starting corrals to elucidate the flowing behavior of polarized crowds by probing its response to boundary motion. We establish that speed information propagates over system-spanning scales through polarized crowds, whereas orientational fluctuations are locally suppressed. Building on these observations, we lay out a hydrodynamic theory of polarized crowds and demonstrate its predictive power. We expect this description of human groups as active continua to provide quantitative guidelines for crowd management.
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Gorrini, Andrea, Stefania Bandini, and Majid Sarvi. "Group Dynamics in Pedestrian Crowds." Transportation Research Record: Journal of the Transportation Research Board 2421, no. 1 (January 2014): 51–56. http://dx.doi.org/10.3141/2421-06.
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Murakami, Hisashi, Claudio Feliciani, and Katsuhiro Nishinari. "Lévy walk process in self-organization of pedestrian crowds." Journal of The Royal Society Interface 16, no. 153 (April 10, 2019): 20180939. http://dx.doi.org/10.1098/rsif.2018.0939.
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Similar to other animal groups, human crowds exhibit various collective patterns that emerge from self-organization. Recent studies have emphasized that individuals anticipate their neighbours' motions to seek their paths in dynamical pedestrian flow. This path-seeking behaviour results in deviation of pedestrians from their desired directions (i.e. the direct path to their destination). However, the strategies that individuals adopt for the behaviour and how the deviation of individual movements impact the emergent organization are poorly understood. We here show that the path-seeking behaviour is performed through a scale-free movement strategy called a Lévy walk, which might facilitate transition to the group-level behaviour. In an experiment of lane formation, a striking example of self-organized patterning in human crowds, we observed how flows of oppositely moving pedestrians spontaneously separate into several unidirectional lanes. We found that before (but not after) lane formation, pedestrians deviate from the desired direction by Lévy walk process, which is considered optimal when searching unpredictably distributed resources. Pedestrians balance a trade-off between seeking their direct paths and reaching their goals as quickly as possible; they may achieve their optimal paths through Lévy walk process, facilitating the emergent lane formation.
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Zhang, Bosi, Youmei Gao, Yong Han, Siyi Liang, Qiaolin Chen, and Zhihong Yu. "Walking characteristics and collision avoidance strategy in bidirectional pedestrian flow: a study focused on the influence of social groups." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 7 (July 1, 2022): 073405. http://dx.doi.org/10.1088/1742-5468/ac7e41.
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Abstract The walking characteristics and collision avoidance strategies in bidirectional pedestrian flow with both individuals and groups under three different pedestrian densities were investigated experimentally in the present study. The results showed that pedestrians formed lanes in bidirectional flow, and the lane number basically increased with pedestrian density. In addition, the lane number was positively related to the number of groups in the first row of the two opposite crowds. Compared with the no-group experiments, the walking speed of pedestrians showed less difference in the experiments with groups. The fundamental diagram of the bidirectional pedestrian flow with groups under different pedestrian density conditions was calculated. Three types of collision avoidance strategies, detouring around conflicting pedestrians, passing through the conflicting group in the middle, and group splitting, were summarised based on the experimental results. The statistical results of the three collision avoidance strategies adopted by different size groups under the low, medium, and high pedestrian density conditions were obtained. It was found that the large group was more likely to split into subgroups when they encountered conflicting pedestrians, while the small group was more likely to detour around the conflicting pedestrians. For the same group size, the larger the pedestrian density, the higher the proportion of groups that would choose to split into subgroups during the collision avoidance process.
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Shahhoseini, Zahra, and Majid Sarvi. "Traffic Flow of Merging Pedestrian Crowds: How Architectural Design Affects Collective Movement Efficiency." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 20 (September 18, 2018): 121–32. http://dx.doi.org/10.1177/0361198118796714.
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The need for developing reliable and rigorous models that can replicate and make predictions of pedestrian crowd evacuations has necessitated an understanding of the impact of architecture on individuals’ interactions with their surroundings and the behavioral rules that govern their movements. Due to the challenges of providing such behavioral data from natural evacuations and previous crowd incidents, simulation-based and laboratory-based evacuation experiments have recently been employed as innovative data-provision approaches to study crowd behavior notably under emergency conditions. This study explores pioneer experiments of emergency escape with a view to investigating the relationship between spatial constraints and collective behavior of human crowds. Here, we make use of two types of empirical and analytical data obtained from a large number of well-controlled laboratory and evacuation simulation experiments. This study presents findings corresponding to how and to what extent the presence of conflicting layouts in egress areas, particularly merging corridors, affect the collective motion of pedestrians. The focus of attention will be on measures of performance at macroscopic level derived from both observations. Our results suggested that the movement patterns observed in both types of experiments are sensitive to the angle between the two merging streams and the symmetry/asymmetry of the merging layouts, with symmetric layouts almost invariably outperforming the asymmetric counterparts. Also, within each symmetry/asymmetry structural type, the angle at which the flows combined with each other affected the efficiency of discharge. Our findings provide further evidence as to the significant role of the architectural structure of the movement area in facilitating the traffic flow of heavy crowds of pedestrians.
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Lian, Liping, Xu Mai, Weiguo Song, Jun Zhang, Kwok Kit Richard Yuen, and Eric Wai Ming Lee. "Characteristics of merging behavior in large crowds." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 1 (January 1, 2022): 013403. http://dx.doi.org/10.1088/1742-5468/ac42cb.
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Abstract Merging pedestrian flow can be observed often at public intersections and locations where two or more channels merge. Because of restrictions on the flow, pedestrian congestion, or even crowd disasters (e.g. Hajj crush 2015) happen easily at these junctions. However, studies on merging behaviors in large crowds remain rare. This paper investigates the merging characteristics of the pedestrian flow with controlled experiments under laboratory conditions. The formation of lanes is observed, and the lane separation width can vary for different density levels. Shannon entropy is used to analyze the utilization of the passage. The space usage in the merging area is most efficient when the width of the two branches is half that of the main corridor. Furthermore, the branch and main channel can mutually bottleneck each other in the large crowds and the flowrates for the upstream, downstream and branches are investigated. This study uses spatiotemporal diagrams to explore the clogging propagation of the merging flow as well as the relationship of the velocity and position. The results can be used as references for the design of public infrastructure and human safety management.
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Chen, Xuewen, Yuanpeng Jia, Xiaoqi Tong, and Zirou Li. "Research on Pedestrian Detection and DeepSort Tracking in Front of Intelligent Vehicle Based on Deep Learning." Sustainability 14, no. 15 (July 28, 2022): 9281. http://dx.doi.org/10.3390/su14159281.
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In order to improve the tracking failure caused by small-target pedestrians and partially blocked pedestrians in dense crowds in complex environments, a pedestrian target detection and tracking method for an intelligent vehicle was proposed based on deep learning. On the basis of the YOLO detection model, the channel attention module and spatial attention module were introduced and were joined to the back of the backbone network Darknet-53 in order to achieve weight amplification of important feature information in channel and space dimensions and improve the representation ability of the model for important feature information. Based on the improved YOLO network, the flow of the DeepSort pedestrian tracking method was designed and the Kalman filter algorithm was used to estimate the pedestrian motion state. The Mahalanobis distance and apparent feature were used to calculate the similarity between the detection frame and the predicted pedestrian trajectory; the Hungarian algorithm was used to achieve the optimal matching of pedestrian targets. Finally, the improved YOLO pedestrian detection model and the DeepSort pedestrian tracking method were verified in the same experimental environment. The verification results showed that the improved model can improve the detection accuracy of small-target pedestrians, effectively deal with the problem of target occlusion, reduce the rate of missed detection and false detection of pedestrian targets, and improve the tracking failure caused by occlusion.
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Van Hauwermeiren, Jeroen, Katrien Van Nimmen, Peter Van den Broeck, and Maarten Vergauwen. "Vision-Based Methodology for Characterizing the Flow of a High-Density Crowd on Footbridges: Strategy and Application." Infrastructures 5, no. 6 (June 25, 2020): 51. http://dx.doi.org/10.3390/infrastructures5060051.
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Obtaining pedestrian trajectories by a vision-based methodology is receiving increasing attention in the literature over recent decades. Within the field of study of human-induced vibrations on footbridges, practical challenges arise when collecting the trajectories of high-density crowds during measurement campaigns. A cheap and robust methodology tackling these issues is presented and applied on a case study consisting of a real-life footbridge occupied with many pedestrians. A static camera setup consisting of low-cost action cameras with limited installation height is used. In addition, a drone camera was employed to collect a limited amount of footage. Pedestrians are equipped with colored hats and detected using a straightforward color-segmenting approach. The measurements are subjected to both systematic and random measurement errors. The influence of the former is theoretically investigated and is found to be of limited importance. The effect of the latter is minimized using a Kalman filter and smoother. A thorough assessment of the accuracy results reveals that the remaining uncertainty is in the order of magnitude of 2 to 3 cm, which is largely sufficient for the envisaged purpose. Although the methodology is applied on a specific case study in the present work, the conclusions regarding the obtained accuracy and employability are generic since the measurement setup can be extended to a footbridge with virtually any length. Moreover, the empirically obtained results of the presented case study should find use in the calibration of pedestrian dynamic models that describe the flow of high-density crowds on footbridges and the further development of load models describing crowd-induced loading.
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Stubenschrott, Martin, Thomas Matyus, Helmut Schrom-Feiertag, Christian Kogler, and Stefan Seer. "Route-Choice Modeling for Pedestrian Evacuation Based on Infrastructure Knowledge and Personal Preferences." Transportation Research Record: Journal of the Transportation Research Board 2623, no. 1 (January 2017): 82–89. http://dx.doi.org/10.3141/2623-09.
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In recent years, pedestrian simulation has been a valuable tool for the quantitative assessment of egress performance in various environments during emergency evacuation. For a high level of realism, an evacuation simulation requires a behavioral model that takes into account behavioral aspects of real pedestrians. In many studies, however, it is assumed that simulated pedestrians have a global knowledge of the infrastructure and choose either a predefined or the shortest route. It is questionable whether this simplification provides realistic results. This study addresses the problem of human-like route-choice behavior for microscopic pedestrian simulations. A route-choice model is presented that considers two concepts: first, the modeling of infrastructure knowledge to represent the variations in the decision-making processes of pedestrians with different degrees of familiarity with the infrastructure (e.g., regular commuters versus first-time visitors). Second, for each pedestrian the internal preference for selecting a certain path can be calibrated to allow the choice for the fastest routes or the ones that are most convenient for the agent (e.g., by avoiding stairs). The approach here uses a hybrid route-choice behavior model composed of a graph-based macrolevel representation of the environment, which is augmented with local information to avoid obstacles and dense crowds in the vicinity. This method was applied with different parameter sets in an evacuation study of a multilevel subway station. The results show the impact of these parameters on evacuation times, use of infrastructure elements, and crowd density at specific locations.
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Boltes, Maik, Juliane Adrian, and Anna-Katharina Raytarowski. "A Hybrid Tracking System of Full-Body Motion Inside Crowds." Sensors 21, no. 6 (March 17, 2021): 2108. http://dx.doi.org/10.3390/s21062108.
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For our understanding of the dynamics inside crowds, reliable empirical data are needed, which could enable increases in safety and comfort for pedestrians and the design of models reflecting the real dynamics. A well-calibrated camera system can extract absolute head position with high accuracy. The inclusion of inertial sensors or even self-contained full-body motion capturing systems allows the relative tracking of invisible people or body parts or capturing the locomotion of the whole body even in dense crowds. The newly introduced hybrid system maps the trajectory of the top of the head coming from a full-body motion tracking system to the head trajectory of a camera system in global space. The fused data enable the analysis of possible correlations of all observables. In this paper we present an experiment of people passing though a bottleneck and show by example the influences of bottleneck width and motivation on the overall movement, velocity, stepping locomotion and rotation of the pelvis. The hybrid tracking system opens up new possibilities for analyzing pedestrian dynamics inside crowds, such as the space requirement while passing through a bottleneck. The system allows linking any body motion to characteristics describing the situation of a person inside a crowd, such as the density or movements of other participants nearby.
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Xu, Han, Xiangxia Ren, Weiguo Song, Jun Zhang, and Rayyan Saidahmed. "Spatial and temporal analysis of the bottleneck flow under different walking states with a moving obstacle." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 1 (January 1, 2023): 013401. http://dx.doi.org/10.1088/1742-5468/aca2a2.
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Abstract The regulation of a moving obstacle on crowd movement offers the possibility to enhance evacuation efficiency in emergency situations. In this paper, a series of controlled experiments are conducted to study the effect of the moving obstacle on crowd dynamics for pedestrians in three different competitive levels, which respectively correspond to three different walking states. The enhancement effects of the moving obstacle on evacuation efficiency for the crowd in the dual-task and high-motivated walking states are confirmed, and the positions of the moving obstacle are crucial. It is found that the moving obstacle diminishes the order of the trajectories for the crowd in the dual-task and normal walking states, while it boosts near the exit for the crowd in the high-motivated walking state. And the moving obstacle makes the linear backward propagations of stop-and-go wave disappear for the crowd in the dual-task and high-motivated walking states, but the frequency of stop behavior increases for the crowd in the dual-task and normal walking states. The profiles of evacuation time show that the moving obstacle impedes the pedestrian flow from the front of the exit and increases evacuation efficiency for the pedestrians near the walls of the exit. The analysis of time headway suggests that the moving obstacle with a gap of 1.0 m or 1.2 m to the exit can reduce the number of the pedestrians waiting near the exit for the crowd in the dual-task and high-motivated walking states. Besides, the gap of 0.8 m between the moving obstacle and the exit makes the conflicts at the exit is increased, but the gap of 1.0 m or 1.2 m makes the number of conflicts at the exit be reduced. This study helps the evacuation management of dense crowds and improves the design of facilities to facilitate pedestrian traffic.
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Yoshida, Junji, Yozo Fujino, and Toshiyuki Sugiyama. "Image Processing for Capturing Motions of Crowd and Its Application to Pedestrian-Induced Lateral Vibration of a Footbridge." Shock and Vibration 14, no. 4 (2007): 251–60. http://dx.doi.org/10.1155/2007/763437.
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An image processing technique to capture motions of crowds is proposed and it is applied to understanding pedestrian-induced lateral vibration in a footbridge. Firstly, an outline of recording sequential images of vibration in the bridge is described and, then an image processing for human-head recognition from a single image of crowd is developed. In this method, conventional template matching techniques with human-head templates are extended by employing some selected templates, an updated search-algorithm and a classifier for clustering. Consequently, more than 50% of human-heads could be identified by the proposed method. Then, motions of detected human-heads, together with the bridge response, are tracked. Finally, interaction between the motions of pedestrians and the vibration of the bridge is discussed, with the emphasis on synchronization between the responses of the pedestrians and the bridge.
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Saberi, Meead, and Hani S. Mahmassani. "Exploring Areawide Dynamics of Pedestrian Crowds." Transportation Research Record: Journal of the Transportation Research Board 2421, no. 1 (January 2014): 31–40. http://dx.doi.org/10.3141/2421-04.
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Appert-Rolland, C., J. Cividini, H. J. Hilhorst, and P. Degond. "Pedestrian Flows: From Individuals to Crowds." Transportation Research Procedia 2 (2014): 468–76. http://dx.doi.org/10.1016/j.trpro.2014.09.062.
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Abdelghany, Ahmed, Khaled Abdelghany, Hani S. Mahmassani, and Saad A. Al-Gadhi. "Microsimulation Assignment Model for Multidirectional Pedestrian Movement in Congested Facilities." Transportation Research Record: Journal of the Transportation Research Board 1939, no. 1 (January 2005): 123–32. http://dx.doi.org/10.1177/0361198105193900115.
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Frequent pedestrian casualties in crowded facilities have brought increasing attention to the study of pedestrian dynamics in such facilities. In this paper, a microsimulation assignment model for multidirectional pedestrian movement in crowds is presented. The model attempts to overcome many limitations of existing models by incorporating various pedestrian behavior rules under a particular set of situations. It also adopts a cellular automata discrete system that allows detailed representation of pedestrians’ walkways and movement areas. The model is applied to the “mataf” system, which is located at the main prayer hall of the holy noble mosque known as Al-Haram Al-Shareef Mosque in Mecca, Saudi Arabia. A set of simulation experiments is designed to illustrate use of the model to study the performance of the mataf system by consideration of different operational conditions as well as different pilgrim behavior rules.
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Alhindi, Afnan, Deem Alyami, Aziza Alsubki, Razan Almousa, Najla Al Nabhan, A. B. M. Alim Al Islam, and Heba Kurdi. "Emergency Planning for UAV-Controlled Crowd Evacuations." Applied Sciences 11, no. 19 (September 27, 2021): 9009. http://dx.doi.org/10.3390/app11199009.
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One of the most challenging problems during disasters involving crowds is pedestrian evacuation. It is very important in such situations to improve survival rates by getting all or most of the people out in the shortest possible time. Technological intervention through augmenting the evacuation process using an unmanned aerial vehicle (UAV) exhibits great potential in improving survival rates, but the exploration of this method is still in its infancy. Therefore, this study explores the potential of utilizing UAVs for crowd management during emergency evacuations. We conducted a rigorous study, using a simulation model featuring four UAVs and differing numbers of pedestrians, with use of two UAV guidance approaches: partial guidance and full guidance. The experimental results suggest that exploiting UAVs in crowd evacuation and following the partial guidance approach can lead to a more efficient evacuation process.
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Liu, Peixin, Xiaofeng Li, Yang Wang, and Zhizhong Fu. "Multiple Object Tracking for Dense Pedestrians by Markov Random Field Model with Improvement on Potentials." Sensors 20, no. 3 (January 22, 2020): 628. http://dx.doi.org/10.3390/s20030628.
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Pedestrian tracking in dense crowds is a challenging task, even when using a multi-camera system. In this paper, a new Markov random field (MRF) model is proposed for the association of tracklet couplings. Equipped with a new potential function improvement method, this model can associate the small tracklet coupling segments caused by dense pedestrian crowds. The tracklet couplings in this paper are obtained through a data fusion method based on image mutual information. This method calculates the spatial relationships of tracklet pairs by integrating position and motion information, and adopts the human key point detection method for correction of the position data of incomplete and deviated detections in dense crowds. The MRF potential function improvement method for dense pedestrian scenes includes assimilation and extension processing, as well as a message selective belief propagation algorithm. The former enhances the information of the fragmented tracklets by means of a soft link with longer tracklets and expands through sharing to improve the potentials of the adjacent nodes, whereas the latter uses a message selection rule to prevent unreliable messages of fragmented tracklet couplings from being spread throughout the MRF network. With the help of the iterative belief propagation algorithm, the potentials of the model are improved to achieve valid association of the tracklet coupling fragments, such that dense pedestrians can be tracked more robustly. Modular experiments and system-level experiments are conducted using the PETS2009 experimental data set, where the experimental results reveal that the proposed method has superior tracking performance.
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Qi, Zhouming, Mian Zhou, Guoqiang Zhu, and Yanbing Xue. "Multiple Pedestrian Tracking in Dense Crowds Combined with Head Tracking." Applied Sciences 13, no. 1 (December 29, 2022): 440. http://dx.doi.org/10.3390/app13010440.
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In order to reduce the negative impact of severe occlusion in dense scenes on the performance degradation of the tracker, considering that the head is the highest and least occluded part of the pedestrian’s entire body, we propose a new multiobject tracking method for pedestrians in dense crowds combined with head tracking. For each frame of the video, a head tracker is first used to generate the pedestrians’ head movement tracklets, and the pedestrians’ whole body bounding boxes are detected at the same time. Secondly, the degree of association between the head bounding boxes and the whole body bounding boxes are calculated, and the Hungarian algorithm is used to match the above calculation results. Finally, according to the matching results, the head bounding boxes in the head tracklets are replaced with the whole body bounding boxes, and the whole body motion tracklets of the pedestrians in the dense scene are generated. Our method can be performed online, and experiments suggested that our method effectively reduces the negative effects of false negatives and false positives on the tracker caused by severe occlusion in dense scenes.
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Warren, William H. "Collective Motion in Human Crowds." Current Directions in Psychological Science 27, no. 4 (July 11, 2018): 232–40. http://dx.doi.org/10.1177/0963721417746743.
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The balletic motion of bird flocks, fish schools, and human crowds is believed to emerge from local interactions between individuals in a process of self-organization. The key to explaining such collective behavior thus lies in understanding these local interactions. After decades of theoretical modeling, experiments using virtual crowds and analysis of real crowd data are enabling us to decipher the “rules of engagement” governing these interactions. On the basis of such results, my students and I built a dynamical model of how a pedestrian aligns his or her motion with that of a neighbor and how these binary interactions are combined within a neighborhood of interaction. Computer simulations of the model generate coherent motion at the global level and reproduce individual trajectories at the local level. This approach has yielded the first experiment-driven, bottom-up model of collective motion, providing a basis for understanding more complex patterns of crowd behavior in both everyday and emergency situations.
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Zhou, Hui, Zhihao Zheng, Xuekai Cen, Zhiren Huang, and Pu Wang. "A Data-Driven Urban Metro Management Approach for Crowd Density Control." Journal of Advanced Transportation 2021 (March 30, 2021): 1–14. http://dx.doi.org/10.1155/2021/6675605.
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Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.
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Brownjohn, James Mark William, and Tao Neng Fu. "Vibration Excitation and Control of a Pedestrian Walkway by Individuals and Crowds." Shock and Vibration 12, no. 5 (2005): 333–47. http://dx.doi.org/10.1155/2005/857247.
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As part of a continuing study on effects of humans on loading and dynamic response of footbridges, a steel frame walkway has been the subject of studies on the effects of multiple pedestrians with respect to loading and response mitigation. Following finite element modeling and experimental modal analysis to identify the low frequency vibration modes likely to be excited by normal walking, the variation of response with pedestrian density and of system damping and natural frequency with occupancy by stationary pedestrians were both studied. The potentially mitigating effect of stationary occupants is still not well understood and the study included direct measurement of damping forces and absorbed energy using a force plate. The various tests showed that energy dissipation measured directly was consistent with the observed change in damping, that vertical and lateral response both varied approximately with square root of number of pedestrians, and that the simple model of a human as a single mass-spring-damper system may need to be refined to fit observed changes in modal parameters with a crowd of humans present. Modal parameter changes with moving pedestrians were small compared to those with stationary pedestrians indicating that within limits, modal parameters for the empty structure could be used in analysis.
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Lui, Andrew Kwok Fai, Yin Hei Chan, and Kevin Hung. "Functional Objects in Urban Walking Environments and Pedestrian Trajectory Modelling." Sensors 23, no. 10 (May 18, 2023): 4882. http://dx.doi.org/10.3390/s23104882.
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Functional objects are large and small physical entities installed in urban environments to offer specific functionalities to visitors, such as shops, escalators, and information kiosks. Instances of the novel notion are focal points of human activities and are significant in pedestrian movement. Pedestrian trajectory modelling in an urban scene is a challenging problem because of the complex patterns resulting from social interactions of the crowds and the diverse relation between pedestrians and functional objects. Many data-driven methods have been proposed to explain the complex movements in urban scenes. However, the methods considering functional objects in their formulation are rare. This study aims to reduce the knowledge gap by demonstrating the importance of pedestrian–object relations in the modelling task. The proposed modelling method, called pedestrian–object relation guided trajectory prediction (PORTP), uses a dual-layer architecture that includes a predictor of pedestrian–object relation and a series of relation-specific specialized pedestrian trajectory prediction models. The experiment findings indicate that the inclusion of pedestrian–object relation results in more accurate predictions. This study provides an empirical foundation for the novel notion and a strong baseline for future work on this topic.
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Schadschneider, Andreas, Ansgar Kirchner, and Katsuhiro Nishinari. "From Ant Trails to Pedestrian Dynamics." Applied Bionics and Biomechanics 1, no. 1 (2003): 11–19. http://dx.doi.org/10.1155/2003/292871.
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This paper presents a model for the simulation of pedestrian dynamics inspired by the behaviour of ants in ant trails. Ants communicate by producing a pheromone that can be smelled by other ants. In this model, pedestrians produce a virtual pheromone that influences the motion of others. In this way all interactions are strictly local, and so even large crowds can be simulated very efficiently. Nevertheless, the model is able to reproduce the collective effects observed empirically, eg the formation of lanes in counterflow. As an application, we reproduce a surprising result found in experiments of evacuation from an aircraft.
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Kruszewski, Paul. "Believable and Reactive Crowds in Next Generation Games." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 2, no. 1 (September 29, 2021): 143–44. http://dx.doi.org/10.1609/aiide.v2i1.18767.
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The creation of life-like believable characters is emerging as the central focus of next-generation game development and is viewed as critical to obtaining true mass-market appeal. Reactive crowd simulation is a critical component in creating believable character. The demo runs on a Xbox 360 and shows the following crowd behaviors. A typical downtown is populated with pedestrians and vehicles. The pedestrians mill about the town staying on the sidewalk and cross only at street corners (although some decide will jay walk from time to time). Occasionally, they will stop to talk with one another. Cars drive around the city and obey the traffic lights. The ambient behaviour is interrupted by traumatic event; in this case a terrorist pulls out a run and starts firing at the crowd who now move into a panic behaviour. Some crowd members run away immediately from the terrorist while others first cower in fear before running away. Crowd members who do not hear the weapon fire but see a panicking pedestrian may also panic or continue about their business depending on how cool they are. Vehicles also flee the terrorist and will drive on sidewalks and over pedestrians to save themselves.
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Mohamad Ali, Mohd Firdaus, Muhamad Salleh Abustan, Siti Hidayah Abu Talib, Ismail Abustan, Noorhazlinda Abd Rahman, and Hitoshi Gotoh. "Psychological distance of pedestrian at the bus terminal area." E3S Web of Conferences 34 (2018): 01036. http://dx.doi.org/10.1051/e3sconf/20183401036.
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Walking is a part of transportation modes that is effective for pedestrian in either short or long trips. All people are classified as pedestrian because people do walk every day and the higher number of people walking will lead to crowd conditions and that is the reason of the importance to study about the behaviour of pedestrian specifically the psychological distance in both indoor and outdoor. Nowadays, the number of studies of crowd dynamics among pedestrian have increased due to the concern about the safety issues primarily related to the emergency cases such as fire, earthquake, festival and etc. An observation of pedestrian was conducted at one of the main bus terminals in Kuala Lumpur with the main objective to obtain pedestrian psychological distance and it took place for 45 minutes by using a camcorder that was set up by using a tripod on the upper floor from the area of observation at the main lobby and the trapped area was approximately 100 m2. The analysis was focused on obtaining the gap between pedestrian based on two different categories, which are; (a) Pedestrian with relationship, and (b) Pedestrian without relationship. In total, 1,766 data were obtained during the analysis in which 561 data were obtained for ‘Pedestrian with relationship’ and 1,205 data were obtained for “Pedestrian without relationship”. Based on the obtained results, “Pedestrian without relationship” had shown a slightly higher average value of psychological distance between them compare to “Pedestrian with relationship” with the results of 1.6360m and 1.5909m respectively. In gender case, “Pedestrian without relationship” had higher mean of psychological distance in all three categories as well. Therefore, it can be concluded that pedestrian without relationship tend to have longer distance when walking in crowds.
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Shahhoseini, Zahra, Majid Sarvi, Meead Saberi, and Milad Haghani. "Pedestrian Crowd Dynamics Observed at Merging Sections: Impact of Designs on Movement Efficiency." Transportation Research Record: Journal of the Transportation Research Board 2622, no. 1 (January 2017): 48–57. http://dx.doi.org/10.3141/2622-05.
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The need for reliable crowd simulation tools has necessitated an accurate understanding of human behavior and the rules that govern their movements under normal and emergency escapes. This paper investigates the dynamics of merging streams of pedestrians. In the merging sections, the interaction between pedestrians and geometric features of merging sections can significantly impede the collective motion and can increase the possibility of flow breakdown, particularly under emergency conditions. Therefore, to create safe and efficient designs, it is important to study human movement characteristics associated with these types of conflicting geometries. In this study, empirical data collected from large numbers of high-density experiments with people at different desired speed levels were used to explore the effect of different merging configurations (i.e., design and angle) on dynamics of merging crowds. For the first time, this study examined the impact of elevated speed regimes (as a behavioral proxy of emergency escapes) on the movement efficiency of crowds in merging sections with different geometric designs. In particular, this study investigated the impact of these conflicting geometric settings on the average waiting time in the system as a measure of movement efficiency. Results suggest that the experienced delay is dramatically greater in asymmetrical setups compared with the delay in symmetrical setups and that the difference is even more pronounced at elevated levels of pedestrians’ desired speed. These findings give significant insights into the implications of inefficient designs of merging sections for pedestrians’ safety, notably when quick movement of crowds is necessary (e.g., in emergencies).
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Kazemzadeh, Khashayar, and Prateek Bansal. "Electric bike navigation comfort in pedestrian crowds." Sustainable Cities and Society 69 (June 2021): 102841. http://dx.doi.org/10.1016/j.scs.2021.102841.
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Moussaïd, Mehdi, Elsa G. Guillot, Mathieu Moreau, Jérôme Fehrenbach, Olivier Chabiron, Samuel Lemercier, Julien Pettré, Cécile Appert-Rolland, Pierre Degond, and Guy Theraulaz. "Traffic Instabilities in Self-Organized Pedestrian Crowds." PLoS Computational Biology 8, no. 3 (March 22, 2012): e1002442. http://dx.doi.org/10.1371/journal.pcbi.1002442.
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Kazemzadeh, Khashayar, Aliaksei Laureshyn, Enrico Ronchi, Carmelo D'Agostino, and Lena Winslott Hiselius. "Electric bike navigation behaviour in pedestrian crowds." Travel Behaviour and Society 20 (July 2020): 114–21. http://dx.doi.org/10.1016/j.tbs.2020.03.006.
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Kaminka, Gal A., and Natalie Fridman. "Simulating Urban Pedestrian Crowds of Different Cultures." ACM Transactions on Intelligent Systems and Technology 9, no. 3 (February 13, 2018): 1–27. http://dx.doi.org/10.1145/3102302.
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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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Yudono, A., Surjono, C. Meidiana, I. Nurika, E. Martati, and S. Wibowo. "Humanitarian engineering approach for re-designing pedestrian traffic inside the lecture building during the new normal COVID-19 pandemic." IOP Conference Series: Earth and Environmental Science 916, no. 1 (November 1, 2021): 012016. http://dx.doi.org/10.1088/1755-1315/916/1/012016.
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Abstract COVID-19 has brought a massive impact on people’s daily activities, office workers have implemented “Working from Home” (WFH), an elementary school to high school students have implemented “Study from Home” (SFH), as well as Campus academic communities’ activities’ implementing Learning from Home. This circumstance has changed daily human behavior for a year. In 2021, upon the completion of a global vaccination program, the situation is followed by a change in the pattern of daily living activities towards “a new normal”, in which direct human interaction is reinstated while still fulfilling health protocols, one of the actions is social distancing. This study examined the detection of pedestrian traffic for the academic community of the Department of Urban and Regional Planning (DURP), Brawijaya University and predicted certain crowds’ spots in the DURP building, using Computer Vision and the integration of Agent-Based Model and Geographical Information Systems Indoor. Furthermore, alternative designs for pedestrians were carried out in the DURP building to prevent the occurrences of crowds in certain spots. The results obtained are that on the 1st Floor of the DURP building, the West and East entrance paths have high traffic, so it is necessary to arrange for the opening of the Southside door as an alternative for pedestrian access. Likewise, for the 2nd Floor, the opening of the south gate contributes to minimizing crowd spots. All in all, the blended learning process through face-to-face learning at students grades 1 and 2, then online learning at students grades 3 and 4 might minimize the potential Covid-19 transmission facing a new normal higher education learning process.
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Seitz, Michael J., Nikolai W. F. Bode, and Gerta Köster. "How cognitive heuristics can explain social interactions in spatial movement." Journal of The Royal Society Interface 13, no. 121 (August 2016): 20160439. http://dx.doi.org/10.1098/rsif.2016.0439.
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The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as ‘stop if another step would lead to a collision’ or ‘follow the person in front’. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour.