Crowd Data Visualization and Simulation

Diaz, Leonel Antonio Toledo; Rivas, Ivan Rivalcoba; Rodriguez, Krely; Rudomín, Isaac

doi:10.1016/j.procs.2018.10.201

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…Simulations are used to assist experts in the planning phase. Diaz et al [56] developed a system that can handle interactions with pedestrians involving the visualization of environments. The system computes a mesh for any given zone in the urban environment, doing calculations using shaders in the GPU.…”

Section: Crowd Managementmentioning

confidence: 99%

In-Depth Survey to Detect, Monitor and Manage Crowd

et al. 2020

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Crowd management is a flourishing, active research area and must be given attention due to the potential losses, disasters, and accidents that could occur if it were neglected. For the last decade, the crowd management field has witnessed significant advancements; however, more investigative work is still needed. The integration of different crowd detection and monitoring techniques can enhance the control and the performance compared to those of more limited stand-alone techniques. Crowd management encompasses an entire process, from the monitoring stage through the decision support system stage. This sector involves accessing and interpreting information sources, predicting crowd behavior, and deciding on the use of a range of possible interventions based on context. This paper shows a fresh conclusive review of the concept of the crowd, discussing it from several perspectives in light of its defining characteristics, its risks, and tragedies, which may occur due to challenges faced during crowd management, where these conclusions are based on a massive number of scholarly articles that were newly published. Besides, a systematic discussion is shown concerning the steps of managing a crowd, including crowd detection, in which several new methods are reviewed, followed by illustrating both direct and indirect approaches to crowd monitoring and tracking monitoring. The primary purpose of this review is to establish a comprehensive understanding of crowdrelated processes. Moreover, it aims to find research gaps to overcome the limitations of using stand-alone techniques in each process and provide support to other researchers' future work.

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Section: Crowd Managementmentioning

confidence: 99%

In-Depth Survey to Detect, Monitor and Manage Crowd

et al. 2020

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Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management

Yasufuku,

Takahashi

2024

JDR

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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 Dome, we demonstrated that capturing pedestrian flow allows for accurate predictions of congestion at the nearest train station up to 10 min in advance. Moreover, the time required to predict the situation 20 min ahead for 3,000 agents was 1 min and 35 s, confirming the feasibility of real-time processing. To enhance the accuracy and reliability of the simulation results, a sensitivity analysis considering errors in pedestrian flow measurement revealed that simple linear models cannot capture the complexity of crowd dynamics adequately. Notably, the agent-based simulation replicated stop-and-go wave patterns observed in actual measurements under specific crowd conditions, confirming the advantage of using agent-based simulations. Finally, we proposed a method that enables facility managers and security personnel to conduct a more comprehensive evaluation. This method integrates their existing experience with the aggregated display of multiple simulation results, which includes consideration of errors in pedestrian flow measurement through a visualization platform.

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Crowd Data Visualization and Simulation

Cited by 2 publications

References 8 publications

In-Depth Survey to Detect, Monitor and Manage Crowd

In-Depth Survey to Detect, Monitor and Manage Crowd

Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management

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