Bibliographies thématiques / Crowd, Pedestrian, Proxemics, Simulation

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Littérature scientifique sur le sujet « Crowd, Pedestrian, Proxemics, Simulation »

Auteur : Grafiati
Publié le 9 mars 2023
Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Crowd, Pedestrian, Proxemics, Simulation"

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

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Crowd simulation is used in evacuation and crowd safety inspections and in the study of the performance of crowd systems and animations. Cellular automata are extensively utilized in crowd modeling. In regular cellular automata models, each pedestrian occupies a single cell with the size of a pedestrian body. The movements of pedestrians resemble those of chess pieces on a chessboard because the space is divided into relatively large cells. Furthermore, all pedestrians feature the same body size and speed. This study proposes a fine grid cellular automata model that uses small cells and allows
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Siamak, Sarmady, Haron Fazilah, and Zawawi Talib Abdullah. "Simulation of pedestrian movements using a fine grid cellular automata model." International Journal of Artificial Intelligence (IJ-AI) 11, no. 4 (2022): 1197–212. https://doi.org/10.11591/ijai.v11.i4.pp1197-1212.

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Crowd simulation is used in evacuation and crowd safety inspections and in the study of the performance of crowd systems and animations. Cellular automata are extensively utilized in crowd modeling. In regular cellular automata models, each pedestrian occupies a single cell with the size of a pedestrian body. The movements of pedestrians resemble those of chess pieces on a chessboard because the space is divided into relatively large cells. Furthermore, all pedestrians feature the same body size and speed. This study proposes a fine grid cellular automata model that uses small cells and allows
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Li, Cuiling, Rongyong Zhao, Chuanfeng Han, Rahman Arifur, Yunlong Ma, and Qiong Liu. "Dynamic Disturbance Propagation Model of Pedestrian Panic Behaviors and Lyapunov-Based Crowd Stability Analysis." Applied Sciences 13, no. 21 (2023): 11762. http://dx.doi.org/10.3390/app132111762.

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In public places, pedestrian panic behaviors have received increasing attention due to their dangerous impact on normal pedestrian flow. To address this issue, this study considered crowd panic behaviors as two-dimensional Gaussian disturbances quantitatively triggered by accidents and analyzed the stability of the pedestrian crowd based on Lyapunov criterion. First, this study established a two-dimensional static model for the disturbance pressure in a crowd. Then, a dynamic disturbance–propagation model (DPM) of crowd panic behaviors was proposed based on the conservation law of fluid dynami
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Zanlungo, Francesco, Zeynep Yucel, Claudio Feliciani, Katsuhiro Nishinari, and Takayuki Kanda. "Congestion Number Analysis of Cross-Flow Dynamics: Experimental Data and Simulations." Collective Dynamics 9 (May 17, 2024): 1–8. http://dx.doi.org/10.17815/cd.2024.153.

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We recently proposed the "Congestion Number" (CN) as a metricto evaluate the state of a pedestrian crowd. Such metric, whose definition is based on the gradient of the rotor of the crowd velocity field, appears to provide additional information with respect to traditional metrics based on pedestrian density and flow. We also published two works on the dynamics of orthogonally crossing pedestrian flows under different density regimes. In the first manuscript we analysed experimental data by using traditionalobservables such as density, velocity and relative position between pedestrians, along w
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Vizzari, Giuseppe, and Thomas Cecconello. "Pedestrian Simulation with Reinforcement Learning: A Curriculum-Based Approach." Future Internet 15, no. 1 (2022): 12. http://dx.doi.org/10.3390/fi15010012.

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Pedestrian simulation is a consolidated but still lively area of research. State of the art models mostly take an agent-based perspective, in which pedestrian decisions are made according to a manually defined model. Reinforcement learning (RL), on the other hand, is used to train an agent situated in an environment how to act so as to maximize an accumulated numerical reward signal (a feedback provided by the environment to every chosen action). We explored the possibility of applying RL to pedestrian simulation. We carefully defined a reward function combining elements related to goal orient
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Yasufuku, Kensuke, and Akira Takahashi. "Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management." Journal of Disaster Research 19, no. 2 (2024): 248–55. http://dx.doi.org/10.20965/jdr.2024.p0248.

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Crowd management at large-scale events and specific facilities is a critical issue from the perspectives of safety and service quality improvement. Traditional methods for crowd management often rely on empirical knowledge, which has limitations in quickly grasping the on-site situation and making decisions on the spot. In this study, we developed a real-time crowd flow prediction and visualization platform incorporating an agent-based crowd simulation and an advanced crowd management system called crowd management platform as a service. In a case study focused on the area around the Tokyo Dom
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Qiu, Fasheng, and Xiaolin Hu. "Modeling group structures in pedestrian crowd simulation." Simulation Modelling Practice and Theory 18, no. 2 (2010): 190–205. http://dx.doi.org/10.1016/j.simpat.2009.10.005.

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

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Pedestrian flow simulations play a pivotal role in urban planning, transportation engineering, and disaster response by enabling the detailed analysis of crowd dynamics and walking behavior. While physical models such as the Social Force model and Boids have been widely used, they often struggle to replicate complex inter-agent interactions. On the other hand, reinforcement learning (RL) methods, although adaptive, suffer from limited interpretability due to their opaque policy structures. To address these limitations, this study proposes a pedestrian simulation framework based on the Anticipa
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Liu, Yuanyuan, and Toshiyuki Kaneda. "Using agent-based simulation for public space design based on the Shanghai Bund waterfront crowd disaster." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 34, no. 2 (2020): 176–90. http://dx.doi.org/10.1017/s0890060420000049.

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

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GORRINI, ANDREA. "Empirical studies and computational results of a proxemic - based model of pedestrian crowd dynamics." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/50254.

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The thesis work is organized in two main parts. The first includes a review of the social science framework about crowd dynamics and proxemics, and the methodological approach. The second part consists of several empirical studies. A summary of the contents is provided as follows. Starting from the pioneering study of Gustave Le Bon (1897), the social science contributions about crowds are reviewed in Chapter 2 (Contagion-Transformation Theory, Elaborated Social Identity Model, Emergent Norm Theory, Affiliative Approach). Chapter 3 presents the proxemic theory, with reference to the notion of
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MANENTI, LORENZA ALESSANDRA. "Agent-based proxemic dynamics: crowd and groups simulation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/42374.

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Considering the general overview on the Pedestrian Dynamics area, this thesis is focused in the area of pedestrian dynamics simulation, with the goal to study the phenomenon of groups as constitutive elements that compose a crowd, analyzing if their presence influences the dynamics of pedestrian flow and evaluating the impact of their contribution.
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Bisagno, Niccol&#242. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.

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Crowds of people are gathering at multiple venues, such as concerts, political rallies, as well as in commercial malls, or just simply walking on the streets. More and more people are flocking to live in urban areas, thus generating a lot of scenarios of crowds. As a consequence, there is an increasing demand for automatic tools that can analyze and predict the behavior of crowds to ensure safety. Crowd motion analysis is a key feature in surveillance and monitoring applications, providing useful hints about potential threats to safety and security in urban and public spaces. It is well known
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Bisagno, Niccolò. "On simulating and predicting pedestrian trajectories in a crowd." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/256722.

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Crowds of people are gathering at multiple venues, such as concerts, political rallies, as well as in commercial malls, or just simply walking on the streets. More and more people are flocking to live in urban areas, thus generating a lot of scenarios of crowds. As a consequence, there is an increasing demand for automatic tools that can analyze and predict the behavior of crowds to ensure safety. Crowd motion analysis is a key feature in surveillance and monitoring applications, providing useful hints about potential threats to safety and security in urban and public spaces. It is well kno
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Qiu, Fasheng. "A Framework for Group Modeling in Agent-Based Pedestrian Crowd Simulations." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/cs_diss/56.

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Pedestrian crowd simulation explores crowd behaviors in virtual environments. It is extensively studied in many areas, such as safety and civil engineering, transportation, social science, entertainment industry and so on. As a common phenomenon in pedestrian crowds, grouping can play important roles in crowd behaviors. To achieve more realistic simulations, it is important to support group modeling in crowd behaviors. Nevertheless, group modeling is still an open and challenging problem. The influence of groups on the dynamics of crowd movement has not been incorporated into most existing cro
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Nishinari, Katsuhiro, Satoshi Kokubo, and Kazuhiro Yamamoto. "Simulation for pedestrian dynamics by real-coded cellular automata (RCA)." Elsevier, 2007. http://hdl.handle.net/2237/20045.

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Sorrentino, Luigi. "Simulation and optimization of crowd dynamics using a multiscale model." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/318.

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2010 - 2011<br>In the last decades, the modeling of crowd motion and pedestrian .ow has attracted the attention of applied mathematicians, because of an increasing num- ber of applications, in engineering and social sciences, dealing with this or similar complex systems, for design and optimization purposes. The crowd has caused many disasters, in the stadiums during some major sporting events as the "Hillsborough disaster" occurred on 15 April 1989 at Hills- borough, a football stadium, in She¢ eld, England, resulting in the deaths of 96 people, and 766 being injured that remains the d
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Cabrero, Daniel Beatriz. "Automating crowd simulation: from parameter tuning to dynamic context-to-policy adaptation." Doctoral thesis, Universitat Pompeu Fabra, 2022. http://hdl.handle.net/10803/673251.

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Computer-generated crowds are becoming more and more frequent in films, video games and safety assessment applications. Many crowd simulation algorithms exist to address the needs of this diverse range of industries. Even though the underlying principles are similar, there are large differences between the resulting synthetic trajectories. Each algorithm has strengths and weaknesses that need to be weighted, and appropriate parameter values for them must be selected as well. These are not easy tasks and Machine Learning algorithms are often used to guide these decisions. In this work we study
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Berton, Florian. "Immersive virtual crowds : evaluation of pedestrian behaviours in virtual reality." Thesis, Rennes 1, 2020. http://www.theses.fr/2020REN1S056.

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La réalité virtuelle (RV) est devenu un outil de plus en plus utilisé afin d'étudier le comportement humain. En effet, son utilisation permet d'avoir un contrôle absolu sur les conditions expérimentales et de reproduire le même stimulus pour tous les participants. Dans cette thèse, nous utilisons la RV pour étudier le comportement piétons dans les foules afin par la suite d'améliorer les simulateurs de foules. En particulier nous nous intéressons à l'analyse couplée de la marche et du regard pour pouvoir comprendre et modéliser le voisinage d'interaction lors de la navigation. Dans nos premier
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Kabalan, Bachar. "Dynamique des foules : modélisation du mouvement des piétons et forces associées engendrées." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1126/document.

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Que ce soit dans une rue commerçante, un supermarché ou un aéroport, les phénomènes de foule sont incontournables et nous affecte au quotidien. Elle constitue un système complexe dont la dynamique collective, résultant des interactions individuelles, est difficile à appréhender et a toujours intrigué les scientifiques de différents domaines. Grâce au progrès technologique, il est aujourd'hui possible de modéliser les mouvements de foule et de les reproduire en simulation. Les simulations de mouvement de foule permettent aux chercheurs de plusieurs disciplines, comme les sciences sociales ou la
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Chapitres de livres sur le sujet "Crowd, Pedestrian, Proxemics, Simulation"

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Pettré, Julien, David Wolinski, and Anne-Hélène Olivier. "Velocity-Based Models for Crowd Simulation." In Pedestrian and Evacuation Dynamics 2012. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02447-9_88.

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Klüpfel, Hubert. "Models for Crowd Movement and Egress Simulation." In Pedestrian and Evacuation Dynamics 2008. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04504-2_65.

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Renc, Paweł, Maciej Bielech, Tomasz Pęcak, et al. "HPC Large-Scale Pedestrian Simulation Based on Proxemics Rules." In Parallel Processing and Applied Mathematics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43222-5_43.

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Paris, Sébastien, Delphine Lefebvre, and Stéphane Donikian. "SIMULEM: Introducing Goal Oriented Behaviours in Crowd Simulation." In Pedestrian and Evacuation Dynamics 2008. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04504-2_40.

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Münchow, Stefan, Ia Enukidze, Stefan Sarstedt, and Thomas Thiel-Clemen. "WALK: A Modular Testbed for Crowd Evacuation Simulation." In Pedestrian and Evacuation Dynamics 2012. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02447-9_118.

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Peng, Gao, and Xu Ruihua. "3-Tier Architecture for Pedestrian Agent in Crowd Simulation." In Pedestrian and Evacuation Dynamics 2008. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04504-2_53.

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Seer, Stefan, Norbert Brändle, and Dietmar Bauer. "Design of Decision Rules for Crowd Controlling Using Macroscopic Pedestrian Flow Simulation." In Pedestrian and Evacuation Dynamics 2008. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04504-2_52.

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Cui, Q., M. Ichikawa, T. Kaneda, and H. Deguchi. "A Dynamic Simulation on Crowd Congestion in Large-Scale Terminal Station Complex in an Official Announcement Advisory Information." In Pedestrian and Evacuation Dynamics. Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-9725-8_34.

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Agrawal, Subham, Nils Dengler, and Maren Bennewitz. "Evaluating Robot Influence on Pedestrian Behavior Models for Crowd Simulation and Benchmarking." In Lecture Notes in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3519-1_34.

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Li, Mingkai, Peter Kok-Yiu Wong, Cong Huang, and Jack C. P. Cheng. "Indoor Trajectory Reconstruction Using Building Information Modeling and Graph Neural Networks." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.89.

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Trajectory reconstruction of pedestrian is of paramount importance to understand crowd dynamics and human movement pattern, which will provide insights to improve building design, facility management and route planning. Camera-based tracking methods have been widely explored with the rapid development of deep learning techniques. When moving to indoor environment, many challenges occur, including occlusions, complex environments and limited camera placement and coverage. Therefore, we propose a novel indoor trajectory reconstruction method using building information modeling (BIM) and graph ne
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Actes de conférences sur le sujet "Crowd, Pedestrian, Proxemics, Simulation"

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Li, Tianlin, Yiping Yao, Wenjie Tang, and Feng Yao. "A Hybrid Pedestrian Motion Modeling Approach for Crowd Simulation." In 2017 10th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2017. http://dx.doi.org/10.1109/iscid.2017.133.

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Li, Shiwei, and Huimin Niu. "Simulation of Pedestrian Evacuation Flow Based on Crowd Space." In Fifth International Conference on Transportation Engineering. American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479384.192.

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Butenuth, Matthias, Florian Burkert, Florian Schmidt, et al. "Integrating pedestrian simulation, tracking and event detection for crowd analysis." In 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). IEEE, 2011. http://dx.doi.org/10.1109/iccvw.2011.6130237.

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Zhou, Yayun, Wolfram Klein, and Hermann Georg Mayer. "Guideline for Crowd Evacuation Simulation - Validation of a Pedestrian Simulator with RiMEA Test Scenarios." In 4th International Conference on Smart Cities and Green ICT Systems. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005436700350042.

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Rimboux, Antoine, Rob Dupre, Eldriona Daci, et al. "Smart IoT Cameras for Crowd Analysis based on augmentation for automatic pedestrian detection, simulation and annotation." In 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS). IEEE, 2019. http://dx.doi.org/10.1109/dcoss.2019.00070.

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Mohammed, Shabna Sayed, Charitha Dias, Wael Alhajyaseen, and Mohammed Yousef Alqaradawi. "Exploring Crowd Management and Evacuation Strategies using Microscopic Pedestrian Simulation: A Case Study of Souq Waqif." In The 2nd International Conference on Civil Infrastructure and Construction. Qatar University Press, 2023. http://dx.doi.org/10.29117/cic.2023.0130.

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Rojas, Francisco Arturo, and Hyun Seung Yang. "Immersive human-in-the-loop HMD evaluation of dynamic group behavior in a pedestrian crowd simulation that uses group agent-based steering." In the 12th ACM SIGGRAPH International Conference. ACM Press, 2013. http://dx.doi.org/10.1145/2534329.2534336.

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Liang, Jing, Utsav Patel, Adarsh Jagan Sathyamoorthy, and Dinesh Manocha. "Crowd-Steer: Realtime Smooth and Collision-Free Robot Navigation in Densely Crowded Scenarios Trained using High-Fidelity Simulation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/583.

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We present a novel high fidelity 3-D simulator that significantly reduces the sim-to-real gap for collision avoidance in dense crowds using Deep Reinforcement Learning (DRL). Our simulator models realistic crowd and pedestrian behaviors, along with friction, sensor noise and delays in the simulated robot model. We also describe a technique to incrementally control the randomness and complexity of training scenarios to achieve better convergence and generalization capabilities. We demonstrate the effectiveness of our simulator by training a policy that fuses data from multiple perception sensor
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Stuart, Daniel, Keith Christensen, Anthony Chen, Ke-Cai Cao, Caibin Zeng, and YangQuan Chen. "A Framework for Modeling and Managing Mass Pedestrian Evacuations Involving Individuals With Disabilities: Networked Segways as Mobile Sensors and Actuators." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12652.

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Based on our previous work on Mobile Actuator and Sensor Network, Applied Fractional Calculus, Sensor Networks and BUMMPEE (Bottom-Up Modeling of Mass Pedestrian flows implications for the Effective Egress of individuals with disabilities), a general framework is proposed for modeling and managing Mass Pedestrian Evacuations (MPE) in this paper. A distinctive feature compared with previous work is the incorporation of Individuals with Disabilities (IwDs) in understanding modeling and control of mass pedestrians evacuations. Networked Segway Supported Responders (NSSR) have been firstly employe
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