Validation of Crowd Models Including Social Groups

Köster, Gerta; Treml, Franz; Seitz, Michael; Klein, Wolfram

doi:10.1007/978-3-319-02447-9_87

Cited by 21 publications

(23 citation statements)

References 16 publications

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“…SGN is thus well-suited for gaming and simulation applications that require believable and efficient group behavior for virtual pedestrians. [Köster et al 2014] for individuals and for groups of 2 and 4, and the ground-truth data for individuals as obtained by [Liddle et al 2011]. Bottom: The frame rates we achieved with a serial and parallel execution of SGN for 1980 agents and different group sizes.…”

Section: Discussionmentioning

confidence: 99%

“…The agents have to evacuate the room through the exit. This experimental setup was proposed by [Köster et al 2014]. It is based on a controlled laboratory experiment performed by [Liddle et al 2011].…”

Section: Methodsmentioning

confidence: 99%

“…We measured the evacuation times achieved by our SGN method, by Moussaïd et al [2010; and by [Köster et al 2014]. We set the radius of each agent to 0.2 m. All other settings were kept as described in Section 5.1.…”

Section: Evacuation Timesmentioning

confidence: 99%

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Adding sociality to virtual pedestrian groups

Jaklin

Kremyzas

Gerærts

2015

Proceedings of the 21st ACM Symposium on Virtual Reality Software and Technology

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We present a new method, Social Groups and Navigation (SGN), to simulate the walking behavior of small pedestrian groups in virtual environments. SGN is the first method to simulate group behavior on both global and local levels. We define quantitative metrics to measure the coherence and the sociality of a group based on existing empirical data of real crowds. SGN is designed to let groups stay in coherent and social formations without explicitly modeling such formations. For groups of four, SGN generates between 13% and 53% more socially-friendly behavior than existing methods, measured over the lifetime of a group in the simulation. For groups of three, the gain is between 15% and 31%, and for groups of two, the gain is between 1% and 4%. SGN can be used with any existing global path planner and any existing path following method. Experiments show that SGN enables the simulation of thousands of agents in real time. Due to its flexible design, it can be easily integrated into a larger crowd simulation framework.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Adding sociality to virtual pedestrian groups

Jaklin

Kremyzas

Gerærts

2015

Proceedings of the 21st ACM Symposium on Virtual Reality Software and Technology

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“…When stress is experienced by a group, affiliation could lead to an urge to maintain social bonds by gathering and moving together (Sime (1985)). The effect is highlighted by Köster et al (2014Köster et al ( , p. 1051: "the need to associate with family and friends may dominate over flight instincts." By seeking closer proximity with group members, people also seek for orientation and support ).…”

Section: Group Behavior: Affiliation and Leadership In Small Groups Imentioning

confidence: 91%

Human Factors in Evacuation Simulation, Planning, and Guidance

Hofinger¹,

Zinke²,

Künzer³

2014

Transportation Research Procedia

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Evacuation research shows growing interest in human factors and psychology. Before, humans were mostly modelled as homogeneous, without individual emotion, motivation or physical needs. Human factors had mainly been taken into account as physical characteristics or space requirements. In this paper, we give examples of relevant human factors from the literature and our own field research. Human factors include physical, cognitive, motivational and social variables. As yet, there is no validated set of variables most relevant for safe and fast evacuation. Models for classifying human factors from other domains are introduced for use in future research.

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“…The influence of group dynamics on the behaviour of pedestrians and the differences between the behaviour of pedestrians walking in groups and single pedestrians have been presented in several recent works. We refer to [11,41,44,47,36]. In these works experimental studies as well as numerical experiments are presented In this work, we closely follow a procedure for interacting particle systems used, for example, in the description of coherent motion of animal groups such as schools of fish, flocks of birds or swarms of insects, see Ref.…”

mentioning

confidence: 99%

Particle methods for multi-group pedestrian flow

Mahato

Klar

Tiwari

2018

Applied Mathematical Modelling

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Abstract. We consider a multi-group microscopic model for pedestrian flow describing the behaviour of large groups. It is based on an interacting particle system coupled to an eikonal equation. Hydrodynamic multi-group models are derived from the underlying particle system as well as scalar multi-group models. The eikonal equation is used to compute optimal paths for the pedestrians. Particle methods are used to solve the equations on all levels of the hierarchy. Numerical test cases are investigated and the models and, in particular, the resulting evacuation times are compared for a wide range of different parameters.

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Validation of Crowd Models Including Social Groups

Cited by 21 publications

References 16 publications

Adding sociality to virtual pedestrian groups

Adding sociality to virtual pedestrian groups

Human Factors in Evacuation Simulation, Planning, and Guidance

Particle methods for multi-group pedestrian flow

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