Fuzzy and Data-Driven Urban Crowds

Toledo, Leonel; Rivalcoba, Ivan; Rudomín, Isaac

doi:10.1007/978-3-319-93713-7_23

Cited by 5 publications

(2 citation statements)

References 23 publications

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“…The machine can look at training samples from videos and when combined with a deep-neural-network can predict the characteristics of crowd modeling (19)(20)(21)(22). Toledo et al (23) combined data-driven and fuzzy logic to deal with the uncertainty of crowd movement.…”

Section: Uav Shootingmentioning

confidence: 99%

Review of Virtual Simulation of Crowd Motion for Urban Emergency Management

Liu

Chai

2022

Transportation Research Record: Journal of the Transportation R

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With increasing urbanization in China, there are more and more urban crowds, bringing new challenges to public safety management. The analysis and modeling of crowd behavior are important aspects of emergency management in smart cities. This paper reviews and summarizes existing research into crowd behavior simulation and analyzes existing simulation data collection methods. Crowd simulation technology is discussed from three aspects: crowd modeling, motion navigation, and emotion-driven crowd animation. The indicators of the simulation models are analyzed from the perspective of model evaluation. Finally, combined with the status quo, the existing research limitations are analyzed, and the direction of further research into crowd simulation behavior is discussed.

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Section: Uav Shootingmentioning

confidence: 99%

Review of Virtual Simulation of Crowd Motion for Urban Emergency Management

Liu

Chai

2022

Transportation Research Record: Journal of the Transportation R

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“…There are various approaches have been introduced for crowd steering. Among them, machine learning techniques like statistical method [24] and neural network [25]- [27] has been introduced to develop crowd steering. The learning algorithms can produce a virtual character that can cope with a wide range of possible situations without redesigning the virtual characters.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Agent Simulation Evacuation Model Using The Social Force Model: A Large Room Simulation Study

Park

Shiang²,

Loke³

et al. 2022

JOIV : Int. J. Inform. Visualization

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Research on evacuation simulation has received significant attention over the past few decades. Disasters, whether they were caused by nature or by humans, which claimed lives were also the impetus for the establishment of various evacuation studies. Numerous research points to the possibility of simulating an evacuation utilizing the Social Force Model (SFM) and a leading person or leader, but without using the multi-agent architecture. Within the scope of this article, the multi-agent architecture for crowd steering that we suggest will be investigated. The architecture will utilize a model known as the Social Force Model to figure out how evacuees will move around the area. After this step, the model is simulated in NetLogo to determine whether the architecture can model the evacuation scenario. A simulation test is carried out for us to investigate the degree to which the behavior of the original SFM and the message-passing model is comparable to one another. The result demonstrates that the proposed architecture can simulate the evacuation of pedestrians. In addition, the simulation model can simulate utilizing the grouping strategy as well as the no grouping technique. The findings also showed that the model can capture many evacuation patterns, such as an arch-shaped pattern at the opening of the exit.

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