Bibliographies thématiques / Crowd, Pedestrian, Proxemics, Simulation / Articles de revues

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Articles de revues sur le sujet « Crowd, Pedestrian, Proxemics, Simulation »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 10 mars 2023

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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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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 pedestrian bodies to occupy several cells. The model allows the use of different body sizes, shapes, and speeds for pedestrians. The model is also used to simulate the movements of pedestrians toward a specific target. A typical walkway scenario is considered to test and evaluate the proposed model. Pedestrian movements are smooth because of the fine grain discretization of movements, and simulation results match the empirical speed–density graphs with good accuracy.

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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 results more reasonable, the safety and congestion of the path nodes are considered, to plan the shortest evacuation path. Finally, a contagious disease model is introduced to study the impact of emotion contagion on the evacuation process. A crowd evacuation simulation system is developed, and simulations have been carried out in a variety of scenarios. Experiments show that the model can effectively simulate crowd evacuation, providing a powerful reference for building and layout design.

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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 orientation, basic proxemics, and basic way-finding considerations. The proposed approach employs a particular training curriculum, a set of scenarios growing in difficulty supporting an incremental acquisition of general movement competences such as orientation, walking, and pedestrian interaction. The learned pedestrian behavioral model is applicable to situations not presented to the agents in the training phase, and seems therefore reasonably general. This paper describes the basic elements of the approach, the training procedure, and an experimentation within a software framework employing Unity and ML-Agents.

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Alrashed, Mohammed, and Jeff Shamma. "Agent Based Modelling and Simulation of Pedestrian Crowds in Panic Situations." Collective Dynamics 5 (August 12, 2020): A100. http://dx.doi.org/10.17815/cd.2020.100.

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The increasing occurrence of panic stampedes during mass events has motivated studying the impact of panic on crowd dynamics. Understanding the collective behaviors of panic stampedes is essential to reducing the risk of deadly crowd disasters. In this work, we use an agent-based formulation to model the collective human behavior in such crowd dynamics. We investigate the impact of panic behavior on crowd dynamics, as a specific form of collective behavior, by introducing a contagious panic parameter. The proposed model describes the intensity and spread of panic through the crowd. The corresponding panic parameter impacts each individual to represent a different variety of behaviors that can be associated with panic situations such as escaping danger, clustering, and pushing. Simulation results show contagious panic and pushing behavior, resulting in a more realistic crowd dynamics model.

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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 change behavior processing. Meanwhile, it investigates the crowd’s tangential change behavior and its interaction process, revealing the crowd evacuation mechanism of tangential change behavior conditions. Simulation results show that as the crowd density gradually increases, pedestrians exhibit the evolutionary characteristic of “no tangential change ⟶ occasional tangential change ⟶ frequent tangential change ⟶ closely following.” The evacuation speed is obviously influenced by pedestrian’s tangential change behavior and crowd density; when the pedestrian density ρ = 2.0 and ρ = 3.0 , the tangential change behavior not only makes the speed difference and fluctuation between different lanes great but also has the same effect on the average speed of pedestrians. The results of this study can provide theoretical insights into the organization of multichannel evacuation and expand the theoretical space of crowd dynamics in an evacuation.

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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 each individual within the evacuation process. The new method finds an average of the evacuees’ evacuation times of each exit door location; then, based on the average evacuation time, it decides which exit door location would be the best exit door to be used for evacuation by the evacuees. To validate the method, various designs for the evacuation area with various written scenarios were used. The results showed that the model with this new method could predict a proper exit door location among many suggested locations. Lastly, from the results of this research using the integration of this newly proposed method, a new capability for the selected model in terms of safety allowed the right decision in selecting the finest design for the evacuation area among other designs.

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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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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 documents, publicly available videos, and materials of the Shanghai waterfront crowd disaster which happened on December 31, 2014. Based on the investigation, a detailed site survey was conducted and pedestrian flow data were acquired. To test the influence of different spatial layouts, an agent-based simulator is built, following the ASPFver4.0 (Agent Simulator of Pedestrian Flow) pedestrian walking rules. With the surveyed pedestrian flow data, the original spatial layout of the Shanghai Bund waterfront together with five other comparison scenarios are tested, including both space design and crowd management improvements. In the simulation results, the efficiencies of different space design and crowd management solutions are compared. The results show that even simple crowd control measures such as capacity reserve and more proper route planning will allow for a positive improvement in crowd safety. The results also compare the efficiency of different spatial operations and give general suggestions to the problems urban public space designers should consider in high-density environments.

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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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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. In addition, many methods come at a comparatively low cost, even for computationally expensive problems. This allows for their application to larger scenarios. We aim to identify and adapt fitting methods to microscopic crowd simulation in order to explore their potential in pedestrian dynamics. In this work, we first perform a variance-based sensitivity analysis using Sobol’ indices and then crosscheck the results by a derivative-based measure, the activity scores. We apply both methods to a typical scenario in crowd simulation, a bottleneck. Because constrictions can lead to high crowd densities and delays in evacuations, several experiments and simulation studies have been conducted for this setting. We show qualitative agreement between the results of both methods. Additionally, we identify a one-dimensional subspace in the input parameter space and discuss its impact on the simulation. Moreover, we analyze and interpret the sensitivity indices with respect to the bottleneck scenario.

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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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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 decrease after these two thresholds. Pedestrian flow traffic reaches its maximum value at K2. The proportion of unmoving pedestrians will increase and the increased amplitude increases when it reaches at the two thresholds K1 and K2.

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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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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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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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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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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 between pedestrians and an environment. To perform quickly different 2D/3D geometrical queries various spatial indexing techniques are used, allowing fast identification of navigable spaces and proximity checks related to avoidance of people and obstacles in built environments. For example, for a moderate size building having eight floors and a net area of 13,000 m2, it takes only 104 s to extract the required building information to run a simulation. This approach can be used for any building configuration extracting automatically needed features to run pedestrian simulations. In this way, architects, urban planners, fire safety engineers, transport modellers and many other users without the need to manually interact with a building model can perform immediately crowd simulations.

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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 or replicate. Thus, studying these facilities through real-life scenarios is almost impossible. Accordingly, a micro-simulation assignment model for multidirectional pedestrian movement is used for this purpose. The model adopts a Cellular Automata (CA) discrete system, which allows detailed representation of the pedestrians’ walkways in the tunnel. The modeling approach captures crowd dynamics through representation of behavioral decisions of heterogeneous pedestrians at the individual level. Several experiments are conducted to study the pedestrian flow in the proposed tunnel considering different operational scenarios including demand levels, heterogeneous traffic, evacuation scenario, and tunnel blockage. Results show that flow of large pedestrian volumes through a long confined linear structure, such as a tunnel, are subject to the same flow dynamics as we observe with vehicular traffic. In particular, they are subject to the formation of “clumps” and shock waves that can rapidly propagate and lead to inefficient operation, including flow breakdown with stop-and-go waves.

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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 numerical integrations. In particular, the present model accounts for the possibility of reducing the exit time from a room by carefully positioning obstacles that direct the crowd flow.

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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 improve the accuracy of the simulation, was applied to improve the accuracy of numerical simulations of pedestrian flow. Design/methodology/approach The EnKF, one of the data assimilation techniques, was applied to the in-house numerical simulation code for pedestrian flow. Two cases were studied in this study. One was the simplified one-directional experimental pedestrian flow. The other was the real pedestrian flow at the Kaaba in Mecca. First, numerical simulations were conducted using the empirical input parameter sets. Then, using the observation data, the EnKF estimated the appropriate input parameter sets. Finally, the numerical simulations using the estimated parameter sets were conducted. Findings The EnKF worked on the numerical simulations of pedestrian flow very effectively. In both cases: simplified experiment and real pedestrian flow, the EnKF estimated the proper input parameter sets which greatly improved the accuracy of the numerical simulation. The authors believe that the technique such as EnKF could also be used effectively in other fields of computational engineering where simulations and data have to be merged. Practical implications This technique can be used to improve both design and operational implementations of pedestrian and crowd dynamics predictions. It should be of high interest to command and control centers for large crowd events such as concerts, airports, train stations and pilgrimage centers. Originality/value To the authors’ knowledge, the data assimilation technique has not been applied to a numerical simulation of pedestrian flow, especially to the real pedestrian flow handling millions pedestrian such as the Mataf at the Kaaba. This study validated the capability and the usefulness of the data assimilation technique to numerical simulations for pedestrian flow.

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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 of previous pedestrians affects decision making process of the pedestrians coming later. Unlike pedestrians leaving footprint in mud or turf, pedestrians leave no marks on hard surface. We consider each step of pedestrian moving on hard surface as a mutable invisible footprint which further forms a virtual trail. We first build a model to simulate how the invisible footprint forms and evolves on hard surface, upon which an agent-based crowd simulation model is then built to simulate how pedestrian makes trade-off between the invisible trajectory and the shortest path. The proposed model is validated by case studies with two scenarios. The simulation results indicate that we are able to simulate the impact on pedestrian’s decision making by the invisible footprint.

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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 (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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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 pedestrian simulation with a hybrid physical–digital interface. Based on this configuration, we explore requirements of the early design stages and accordingly discuss concepts for interaction, simulation, and visualization. The prototype blends user inputs with intuitive design interactions, adapts the simulation process to qualitative and dynamic negotiations, and presents results immediately in the discussed context. Thus, it aligns crowd simulation with contingent collaborations and reveals its potential in the early design stages.

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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. It concluded that the model is effective and adapted to large scale systems.

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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, route choice etc. However, pedestrian movement in urban areas and the interactions between pedestrians and vehicles have received notably less attention. A number of challenges to be addressed in future research are outlined: first, the need to and account for the hierarchical behavioural model of road users (strategic / tactical / operational behaviour); second, the need for appropriate description and parameterization of vehicle and pedestrian networks and their crossing points; third, the need to exploit in the simulation models the results of statistical and probabilistic models, which offer valuable insight in the determinants of pedestrian behaviour. In each case, recent studies towards addressing these challenges are outlined.

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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 perceived by the pedestrian is large then other exit during the escape process. The model is useful to study the pedestrian’s behavior during the emergency evacuation, and helpful for safe layout of the public facilities.

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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, traffic efficiency, speed, and density were explored using different design models. Results showed that optimization methods such as the design with a 45° funnel, broken guardrail, concaves, and column on the left had significant optimal effects. The optimization methods used in this study would help to implement bottlenecks in subway stations and provide design suggestions to subway designers.

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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 can effectively describe a real evacuation.

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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 resolve this issue, a path planning algorithm has been developed with a novel method for satisfying the arrival-order constraints. The time constraint we suggest is the temporal duration for each character, specifying the order in which they arrive at their target positions. In addition to the algorithm that guarantees the arrival order of objects, a new user interface is suggested for setting up the arrival order. Through several experiments, the proposed algorithm was verified, and can successfully find collision-free paths, while satisfying the time constraint set by the new user interface. Given the available literature, the suggested algorithm and the interface are the first that support arrival order, and their usability is proven by user studies.

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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-making ability. Then, according to the preference of the escapees, the personnel decision-making in each stage is divided into two types: stay and escape. Finally, multiple influencing factors are selected to construct the regression equation for prediction of the escape opportunity. The results show that: (1) Choices of escape opportunity are divided into several stages, which are affected by the pedestrian individual risk tolerance, risk categories strength, distance from danger, and reaction of the neighborhood crowd. (2) There are many important factors indicating the pedestrian individual risk tolerance, in which Gen, Group, Time and Mode are a positive correlation, while Age and Zone are a negative correlation. (3) The analysis of the natural response rate of different evacuation strategies shows that 19.81% of people evacuate immediately. The research in this paper can better protect public safety and promote the normal activities of the population.

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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 interaction mechanism between pedestrians, and the decision-making of one pedestrian regarding route choice is subject to the environment factor and interaction payoffs between his neighbors. The influences of the intensity of interaction between pedestrians, the willingness to cooperate, the number of groups, the size of groups, and the initial distribution pattern of groups on the evacuation dynamics and cooperation evolution of the crowd are discussed. Simulation results show that it is beneficial to the evacuation efficiency and the formation of cooperation behaviors when pedestrians have a low intensity of interaction. As the willingness of large groups to cooperate is high, an increase in group’ sizes and numbers can improve the cooperation fraction of the crowd but prolongs evacuation time. Groups in the crowd gathered together initially negatively affect the evacuation efficiency of the crowd.

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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 preference were simultaneously considered. Specifically, simulations including pedestrian counter flow with preference (Case A), with conflicting preference (Case B), and without preference (Basic case) were performed. Results show that the presented model can capture some essential features of pedestrian counter flow with various walking preference. It is not always necessary to intervene the behavior of pedestrians ’ conflicting preference, since appropriate degree of preference is sometimes beneficial to movement of pedestrians. In addition, with the significant influence of position exchange, the flow in Case A with more orderly motion is more efficient in the context of low density, while the flow in Case B with more frequent interactions is more efficient in the case of high density. The findings in this study will be helpful in crowd management as well as the design and operation of pedestrian facilities.

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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 ensures that the durations of the generated trajectories are minimal and the urgent individuals are collision-free with dynamic obstacles (e.g., dynamic vehicles). In the second step, a pushing model is adopted to simulate the interactions between urgent members and normal ones, which ensures that the computational cost of the optimal trajectory planning is acceptable. The third step is obligated to imitate the interactions among normal members using collision avoidance behavior and flocking behavior. Various simulation results demonstrate that these three steps give realistic crowd phenomenon just like the real world.

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Ma, Ya-Ping, and Hui Zhang. "Simulation study on cooperation behaviors and crowd dynamics in pedestrian evacuation." Chinese Physics B 29, no. 3 (2020): 038901. http://dx.doi.org/10.1088/1674-1056/ab6b14.

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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 made a deep study of relations of parameters such as evacuation time, pedestrian density, exit number and average queuing time to obtain the pedestrian flow characteristic more in line with the reality. The result has shown that there is a great change in the evacuated population in the change of crowded state at the exit, and in the background of high population density, it is beneficial for reducing queuing time to prefer faraway exit to overcrowded exit for evacuation.

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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 considering the statistical characteristics of pedestrian movements, which extends the concept of transition probability in the original lattice gas model to distribution of pedestrian movements’ length in two perpendicular directions. The proposed model is applied to a scenario which is the same as the experiments of the open dataset, and the numerical results demonstrate that the proposed model can reproduce the fundamental diagrams and the transition probability of the experimental dataset well. This study is helpful to understand the statistical characteristics of pedestrian movements and can improve the applicability and accuracy of the lattice gas model.

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Ji, Liqiang, Yongsheng Qian, Junwei Zeng, et al. "Simulation of Evacuation Characteristics Using a 2-Dimensional Cellular Automata Model for Pedestrian Dynamics." Journal of Applied Mathematics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/284721.

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In public places, the high pedestrian density is one of the direct causes leading to crowding and trample disaster, so it is very necessary to investigate the collective and evacuation characteristics for pedestrian movement. In the occupants’ evacuation process, the people-people interaction and the people-environment interaction are sufficiently considered in this paper, which have been divided into the exit attraction, the repulsion force between people, the friction between people, the repulsion force between human and barrier, and the attraction of surrounding people. Through analyzing the existing models, a new occupant evacuation cellular automata (CA) model based on the social force model is presented, which overcomes the shortage of the high density crowd simulation and combines the advantages that CA has sample rules and faster calculating speed. The simulating result shows a great applicability for evacuation under the high density crowd condition, and the segregation phenomena have also been found in the bidirectional pedestrian flow. Besides these, setting isolated belt near the exit or entrance of underpass not only remarkably decreases the density and the risk of tramper disaster but also increases the evacuation efficiency, so it provides a new idea for infrastructure design about the exits and entrances.

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Li, Liang, Hong Liu, and Yanbin Han. "An approach to congestion analysis in crowd dynamics models." Mathematical Models and Methods in Applied Sciences 30, no. 05 (2020): 867–90. http://dx.doi.org/10.1142/s0218202520500177.

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This paper presents a novel approach to quantitatively analyzing pedestrian congestion in evacuation management based on the Hughes and social force models. An accurate analysis of crowds plays an important role in illustrating their dynamics. However, the majority of the existing approaches to analyzing pedestrian congestion are qualitative. Few methods focus on the quantification of the interactions between crowds and individual pedestrians. According to the proposed approach, analytic tools derived from theoretical mechanics are applied to provide a multiscale representation of such 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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Meng, Bo, Ting Liu, and Na Lu. "Research on Crowd Evacuation Simulation in Complex Mountainous Terrain Area Based on Cellular Automata." Applied Mechanics and Materials 644-650 (September 2014): 1391–95. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1391.

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Recently, the variety of emergent events frequently occurring, such as: great environmental pollution, fire and explosion, toxic gas leakage, disserves human’s living environment, and huge economic and property losses, especially in the rural areas of mountain, where always surrounding by gas fields, chemical plants and other potentially dangerous source, the terrain of mountainous is complex, in the event of crises, the safe evacuation of the population will become a very critical issue. In this paper, through the analysis of the existing evacuation model based on the proposed application 3D surface cellular automata method simulation the evacuation processin complex mountainous terrain. The digital elevation model data, road network and characteristics of the pedestrian are integrated initiatively in the 3D surface CA model. The framework for data extraction, procession and application is designed. A Visualization Software System for three-dimensional simulation of pedestrian evacuation is developed. Moreover, through a case study of some gas well, which belongs to the Puguang gas field in the northeastern Sichuan, it is proved that the model presented in this paper can realize 3D simulation of pedestrian evacuation and predict evacuation time. At last the future work of the model is discussed.

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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 challenges and opportunities on empirical studies on the pedestrians complex movements is limited in the literature. The overall aim of this study is to present a systematic review on the empirical data collection for uni- and multidirectional crowd complex movements. We first categorized the complex movements of pedestrian crowd into two general categories, namely, external governed movements and internal driven movements based on the interactions with the infrastructure and among pedestrians, respectively. Further, considering the hierarchy of movement complexity, we decomposed the externally governed movements of pedestrian traffic into several unique movement patterns including straight line, turning, egress and ingress, opposing, weaving, merging, diverging, and random flows. Analysis of the literature showed that empirical data were highly rich in straight line and egress flow while medium rich in turning, merging, weaving, and opposing flows, but poor in ingress, diverging, and random flows. We put emphasis on the need for the future global collaborative efforts on data sharing for the complex crowd movements.

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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 heterogeneity of pedestrians, so as to achieve more accurate simulation and make the research conclusions closer to reality. To be specific, we attempt to determine the cell side length and simulation time step of an initial model parameterized using a dataset of actual pedestrian movements. It allows more than one pedestrian to be in the same cell and stipulates that the utility of pedestrians decreases with the growing number of pedestrians in the cell. The Bayesian Nash equilibrium is applied to analyze the decision-making process of pedestrians and collision avoidance rules and interaction rules of agents are also formulated. A number of areas of further research are discussed.

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Muhammed, Danial A., Soran A. M. Saeed, and Tarik A. Rashid. "A Simulation Model for Pedestrian Crowd Evacuation Based on Various AI Techniques." Revue d'Intelligence Artificielle 33, no. 4 (2019): 283–92. http://dx.doi.org/10.18280/ria.330404.

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Dias, Charitha, Majid Sarvi, Nirajan Shiwakoti, and Martin Burd. "Turning Angle Effect on Emergency Egress: Experimental Evidence and Pedestrian Crowd Simulation." Transportation Research Record: Journal of the Transportation Research Board 2312, no. 1 (2012): 120–27. http://dx.doi.org/10.3141/2312-12.

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Li, Shiwei, and Huimin Niu. "Simulation of Bi-direction Pedestrian Movement in Corridor Based on Crowd Space." Procedia - Social and Behavioral Sciences 138 (July 2014): 323–31. http://dx.doi.org/10.1016/j.sbspro.2014.07.210.

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Wang, Jinghong, Manman Chen, Bowei Jin, Jia Li, and Zhirong Wang. "Propagation characteristics of the pedestrian shockwave in dense crowd: Experiment and simulation." International Journal of Disaster Risk Reduction 40 (November 2019): 101287. http://dx.doi.org/10.1016/j.ijdrr.2019.101287.

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Lin, Jianxin, Rui Song, Jifeng Dai, and Pengpeng Jiao. "Pedestrian Guiding Signs Optimization for Airport Terminal." Discrete Dynamics in Nature and Society 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/125910.

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The pedestrian guiding sign (PGS) is used to lead people within the transportation terminal to their directions efficiently and without boundaries. In this paper, we aim to optimize the guiding signs for people in the comprehensive transportation terminal with a mathematical model, which describes the pedestrian's reaction, judgment, and perception of the outline about the guiding signs, as well as pedestrian's moving status through self-organized characteristic behavior. Furthermore, the model also reflects the information intensity of the guiding signs within the pedestrian's visual field which is taken as the influence level score of PGS. In order to solve the model, cellular automation (CA) is employed to simulate the characteristics of the pedestrians such as crowd moving and sign selection.

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Elzie, ME, Terra, Erika Frydenlund, MS, Andrew J. Collins, PhD, and R. Michael Robinson, PhD. "Conceptualizing intragroup and intergroup dynamics within a controlled crowd evacuation." Journal of Emergency Management 13, no. 2 (2015): 109. http://dx.doi.org/10.5055/jem.2015.0224.

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Social dynamics play a critical role in successful pedestrian evacuations. Crowd modeling research has made progress in capturing the way individual and group dynamics affect evacuations; however, few studies have simultaneously examined how individuals and groups interact with one another during egress. To address this gap, the researchers present a conceptual agent-based model (ABM) designed to study the ways in which autonomous, heterogeneous, decision-making individuals negotiate intragroup and intergroup behavior while exiting a large venue. A key feature of this proposed model is the examination of the dynamics among and between various groupings, where heterogeneity at the individual level dynamically affects group behavior and subsequently group/group interactions. ABM provides a means of representing the important social factors that affect decision making among diverse social groups. Expanding on the 2013 work of Vizzari et al., the researchers focus specifically on social factors and decision making at the individual group and group/group levels to more realistically portray dynamic crowd systems during a pedestrian evacuation. By developing a model with individual, intragroup, and intergroup interactions, the ABM provides a more representative approximation of real-world crowd egress. The simulation will enable more informed planning by disaster managers, emergency planners, and other decision makers. This pedestrian behavioral concept is one piece of a larger simulation model. Future research will build toward an integrated model capturing decision-making interactions between pedestrians and vehicles that affect evacuation outcomes.

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Kim, Daewa, and Annalisa Quaini. "Coupling kinetic theory approaches for pedestrian dynamics and disease contagion in a confined environment." Mathematical Models and Methods in Applied Sciences 30, no. 10 (2020): 1893–915. http://dx.doi.org/10.1142/s0218202520400126.

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The goal of this work is to study an infectious disease spreading in a medium size population occupying a confined environment. For this purpose, we consider a kinetic theory approach to model crowd dynamics in bounded domains and couple it to a kinetic equation to model contagion. The interactions of a person with other pedestrians and the environment are modeled by using tools of game theory. The pedestrian dynamics model allows to weight between two competing behaviors: the search for less congested areas and the tendency to follow the stream unconsciously in a panic situation. Each person in the system has a contagion level that is affected by the people in their neighborhood. For the numerical solution of the coupled problem, we propose a numerical algorithm that at every time step solves one crowd dynamics problem and one contagion problem, i.e. with no subiterations between the two. We test our coupled model on a problem involving a small crowd walking through a corridor.

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Pu, Y. S., S. Srikukenthiran, E. Morrow, A. Shalaby, and W. Klumpenhouwer. "Capacity Analysis of a Passenger Rail Hub Using Integrated Railway and Pedestrian Simulation." Urban Rail Transit 8, no. 1 (2022): 1–15. http://dx.doi.org/10.1007/s40864-021-00162-7.

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AbstractAs the level of passenger demand in rail transit systems increases, major railway stations in urban centres face serious capacity issues. Both analytical and simulation methods have been used to analyse complex station areas; however, prior efforts have only focused on either train or pedestrian movements with over-simplified assumptions that do not properly capture the impact of their interaction on capacity. This study applies an integrated crowd and transit simulation platform “Nexus” to simultaneously study the impact of pedestrian and train movements on the system performance of a complex railway station. Unlike other methods such as sequential simulation methods, the integrated simulation platform permits linkage between commercial-grade simulators. Instead of treating each simulator separately, this integrated method enables detailed modelling of how the train and crowd dynamic interact at station platforms. Such integration aims to explore the interactive effect on both types of movement and enable performance analysis possible only through this combination. To validate the model, a case study is performed on Toronto’s Union Station. Extensive data were collected, processed and input into railway and pedestrian models constructed using OpenTrack and MassMotion, respectively, and integrated via Nexus. Examining scenarios of increased levels of train and passenger volumes, a 9% drop in on-time performance of train operation is observed, while the level of service experienced by passengers on the platform deteriorates significantly due to crowding. Both length and variation in dwell time due to pedestrian movement are recognized as the main factors of performance deterioration, especially when the system approaches capacity limit. The simulation model produces estimates of the practical track-side capacity of the station and associated platform crowding levels, and helps identify locations where passengers experience severe overcrowding, which are not easily obtainable from mathematical models.

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